Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis

Abstract

Children and adolescents with autism spectrum disorder are thought to be more vulnerable to oral diseases than typically developing individuals due to cariogenic dietary habits, self-injurious behaviors, and increased barriers to dental care services. This review aimed to summarize current evidence comparing the oral health status of people diagnosed with and without autism spectrum disorder. Study selection and screening, data extraction, risk of bias assessment, and quality-of-evidence evaluation was conducted using the Grading of Recommendations Assessment Development and Evaluation approach and performed independently by two reviewers. A total of 16 studies were found eligible for qualitative synthesis and 15 were included in quantitative analysis. When comparing children and adolescents diagnosed with and without autism spectrum disorder, significantly higher prevalence of bruxism was identified. Individuals diagnosed with autism spectrum disorder were also found to have significantly lower salivary pH. However, no statistically significant differences in terms of caries prevalence and severity, oral hygiene and periodontal status, prevalence of malocclusion, dental traumatic injuries, as well as salivary flow rate and buffering capacity were found. The quality of evidence of each outcome was graded as very low mainly due to the overall high risk of bias, considerable heterogeneity, and imprecision.

Lay Abstract

Children and adolescents diagnosed with Autism Spectrum Disorder (ASD) are thought to be more vulnerable to oral diseases than typically-developing individuals. This is due to their increased barriers to dental care services, self-harm behaviors and dietary habits that may favor tooth decay. In this review, we summarized the current evidence comparing the oral health status of children and adolescents diagnosed with and without ASD.

After a systematic search in the literature, we found that the salivary pH of individuals diagnosed with ASD was significantly lower, but the results were not clinically significant that can increase their risks to tooth decay. We also found weak evidence suggesting a higher percentage of children and adolescents diagnosed with ASD having the habit of tooth grinding compared with their neurotypical counterparts. When comparing salivary flow rate, tooth decay, gum diseases, tooth malalignment and tooth trauma; no significant differences were found between the two groups.

The findings did not suggest ASD as a predisposing factor to oral diseases: other factors including sugary diet and inadequate oral hygiene may play a more important role. We also call for further research to establish more concrete association between ASD and oral diseases.

Keywords

autism spectrum disorder children and adolescents oral health

Oral health plays a fundamental role in one’s overall health and well-being, bringing substantial impacts especially toward children’s quality of life (Mouradian, 2001; Wilson-Genderson et al., 2007; Wong et al., 2011). Children with special health care needs are often considered as having increased risks to oral diseases (Ramos-Gomez et al., 2010). Children and adolescents with autism spectrum disorder (ASD) are reported to have a propensity to soft, sticky, and sweetened food (Klein & Nowak, 1998; Weddell et al., 2016); frequent snacking between main meals (Collins et al., 2004); as well as being highly selective and habituated to food and drinks of high cariogenicity (Collins et al., 2004; Schreck et al., 2004; Schreck & Williams, 2006). Parents of individuals diagnosed with ASD also commonly describe their children as “slow feeders” (Emond et al., 2010), often holding and pouching food in the mouth (Klein & Nowak, 1998). These dietary patterns and feeding symptoms commonly demonstrated by a majority of individuals diagnosed with ASD are robustly related to an increased caries risk (Moynihan & Petersen, 2004).

Pharmacological management and therapeutic modalities for individuals diagnosed with ASD may also exacerbate their susceptibility to dental caries and other oral diseases. At least one medication is prescribed to 30%–70% of patients diagnosed with ASD for treating the core or associated conditions (Frazier et al., 2011; Murray et al., 2012). Drug classes which are most frequently prescribed include psychostimulants and antipsychotics, mood stabilizers and antiepileptic drugs, and β-adrenergic antagonists and α-adrenergic agonists (Hsia et al., 2014; Myers & Johnson, 2007; Rosenberg et al., 2010): these drugs are strongly associated with reduced salivary flow and buffering capacity (Scully Cbe, 2003; Wolff et al., 2017). Long-term use of sweetened liquid oral medicine in children diagnosed with ASD is also a major etiological factor that predisposes them to rampant caries development (Feigal et al., 1981; Goyal et al., 2016).

Severe behavioral disturbances associated with self-injury, aggression, and tantrums are frequently reported among individuals diagnosed with ASD and often triggered by routine environmental stimuli, excitement, or stress (American Psychiatric Association, 2013). More than 60% of children diagnosed with ASD have self-injurious behaviors ranging from self-pinching, scratching to severe self-biting, and head banging (Rapin & Dunn, 1997), and the prevalence rises with the severity of the disorder (Jaber et al., 2011; Murshid, 2011). Detrimental oral behaviors like bruxism, tongue thrusting, picking at gingiva, and lip biting are also commonly reported (Kopycka-Kedzierawski & Auinger, 2008), which increase their vulnerability to periodontal diseases, dental trauma, and other oral diseases.

Behavioral problems, restraints accredited with associated disabilities, and dental costs have posed major barriers for individuals diagnosed with ASD to access dental care (Brickhouse et al., 2009; Lai et al., 2012). Due to difficulties in sensory processing, exaggerated aversive responses are often expressed by individuals diagnosed with ASD when perceiving visual, auditory, and tactile inputs during dental visits (Markram et al., 2007; Stein et al., 2011). Nonetheless, with the aid of various behavioral management approaches, many individuals diagnosed with ASD can be successfully treated in routine dental settings. Basic behavioral techniques, for instance, tell-show-do, positive reinforcement, and desensitization, are mandatory to accommodate dental therapy to children diagnosed with ASD (Kamen & Skier, 1985; Luscre & Center, 1996; Surabian, 2001). Therapeutic teaching approaches tailor-made for individuals diagnosed with ASD, for instance, visual pedagogy, social stories, and applied behavioral analysis, have shown promising results to aid children diagnosed with ASD in undergoing dental examination and simple preventive treatments (Backman & Pilebro, 1999; Pilebro & Bäckman, 2005; Virues-Ortega et al., 2013; Warren et al., 2011).

However, when autistic children present with high treatment need and display behavioral challenges in relation to non-compliance, hyperactivity, sensory defensiveness, and self-injuries, general anesthesia and advanced behavioral management techniques are usually indicated (Gandhi & Klein, 2014; Klein & Nowak, 1998; Loo et al., 2009). Increased sensory defensiveness and hyperactivity in children diagnosed with ASD also hinder oral hygiene maintenance; typically, parents of children diagnosed with ASD report difficulties to implement oral hygiene practice in their children (Pilebro & Backman, 2005). Individuals diagnosed with ASD, especially children with poor cooperation in dental clinic, are reported to have significantly increased odds of unmet dental needs (Lai et al., 2012). As only a minority of dental colleagues have autism expertise, this poses a dental health risk to autistic individuals, hampering them to access and receive dental treatment and comparable services (Thomas et al., 2018).

Systematic reviews and meta-analyses have identified the prevalence of oral diseases among individuals diagnosed with ASD to be high (Silva et al., 2017; Udhya et al., 2014); however, the results may be affected by the limited number of studies evaluated and other confounders like age range and location; hence, no “case-control” comparisons of their oral health status with typically developing individuals were made. To implement tailor-made oral health promotion programs and policies to address the dental needs among individuals diagnosed with ASD, a more precise estimate of their oral health status compared with typically developing individuals is required. This systematic review aimed to summarize existing evidence to compare the oral health status between children and adolescents diagnosed with and without ASD.

Methods

This review adhered to the criteria mentioned in the MOOSE guidelines (Stroup et al., 2000) and was registered on PROSPERO (registration number CRD42018096508). The following PECO(S) statement was proposed:

(P) Participants were children and adolescents below 19 years old

(E) Exposure was the diagnosis of ASD

(O) Outcome measures included: (1) dental caries experience, (2) oral hygiene and periodontal health status, (3) malocclusion, (4) traumatic dental injuries, (5) bruxism, and (6) salivary flow rate, pH, and buffering capacity

(S) Studies included are case-control observational studies with full-text reports available in English.

Search strategies

A systematic literature search was performed in five electronic databases from inception to March 2018, including CINAHL, Ovid Embase, Ovid MEDLINE, PsycINFO, and Web of Science using MeSH terms and broad keywords. The full search strategy for Ovid Embase or Ovid MEDLINE is presented in Supplemental Material, Appendix 1. A similar search strategy was adapted for the other databases. Hand searches were conducted by screening the reference lists of the included studies from relevant past systematic reviews to ensure no relevant studies were omitted.

Selection of studies

A precursory review by two independent reviewers (P.P.Y.L. and R.D.) was conducted to identify relevant reports, based on their titles and abstracts. After reading the full-text reports, the two reviewers independently selected the potentially eligible articles. For studies with relevant titles, but unavailable abstract, or studies without information relevant to the inclusion criteria, full-text reports were also retrieved to assess its eligibility.

Screening, assembling, and documenting relevant data from included studies were conducted independently during full-text review. Agreement between reviewers was determined using kappa statistics. Disagreements were resolved by discussion and if not a third reviewer (C.K.Y.Y.) was consulted for the final consensus.

Data extraction and management

A standardized data extraction form was used by the two reviewers independently to obtain relevant data from the included studies: data including participants (location, gender, age range, inclusion, and exclusion criteria), exposure (definition and diagnosis of ASD, location of recruitment, number of participants recruited, and evaluated), comparison (medical condition, matching of socioeconomic background, age, and gender), and outcomes (caries prevalence and severity, oral hygiene and periodontal status, malocclusion prevalence, dental traumatic injury prevalence, bruxism prevalence, salivary flow, pH, and buffering capacity).

Measures of effect and missing data

Prevalence of caries, bruxism, malocclusion, and dental injuries were analyzed as the dichotomous outcomes, which odds ratio (OR) and 95% confidence intervals (CIs) were calculated. Mean number of decayed, missing due to decay, and filled teeth and surfaces in permanent dentition (DMFT/DMFS) and primary dentition (dmfs/dmfs); mean number of untreated decayed teeth and surfaces in permanent (DT/DS) and primary dentitions (dt/ds) (Bodecker, 1939); plaque index (PI) and gingival index (GI) (Löe & Silness, 1963; Silness & Löe, 1964); salivary flow rate; and pH were assessed as continuous outcome or were categorized and compared as dichotomous outcomes. Weighted mean difference (WMD) was evaluated if continuous outcomes were recorded with the same units; when different units (e.g. DMFT and DS, dmft/dmfs, DT/DS, dt/ds) of measurement were used, standardized mean difference (SMD) was analyzed. Complete case analyses were used if the missing data were not significantly large enough to alter the magnitude and direction of the estimates, affecting the conclusions to be drawn.

Subgroup analyses

Subgroup analyses were conducted to separately compare the prevalence and severity of caries, oral hygiene and periodontal status, prevalence of malocclusion, dental traumatic injuries, and bruxism in permanent, mixed, and primary dentition, if available.

Assessment of risk of bias of included studies

Risks of bias of each included study were determined based on the risk of bias in non-randomized studies of interventions tool (ROBINS-I tool) generated by Sterne et al. (2016). Each report was evaluated in seven domains of bias guided with respective signaling questions to obtain an overall final judgment. The seven domains include (I) bias due to confounding, (II) bias in selection of participants into the study, (III) bias in classification of interventions, (IV) bias due to deviation from intended interventions, (V) bias due to missing data, (VI) bias in measurement of outcomes, and (VII) bias in selection reported. After summarizing the results in all domains, an overall rating of low, moderate, serious, or critical risk of bias was given to each study.

Data synthesis

Stata version 13.1 was used to perform the meta-analysis. Meta-analysis with fewer than five studies was handled by fixed-effects model, while random-effect model was adopted for analysis with more studies (Deeks et al., 2008; Guyatt et al., 2015). When studies were found to display significant heterogeneity or divergent results, results were presented narratively. Sensitivity analyses were conducted if necessary to determine whether the effect estimate was dependent of any studies with poor validity (Deeks et al., 2008).

Assessment of heterogeneity

Following the Cochrane Handbook for Systematic Reviews of Intervention (Deeks et al., 2008), heterogeneity of outcome results was assessed. I² statistics and chi-square test were used to calculate the amount of heterogeneity and level of significance (p < 0.05). Based on the value of the I² statistics calculated, the outcomes were rated as of considerable (70% through 100%), substantial (50% through 90%), moderate (30% through 60%), or unimportant heterogeneity (less than 40%).

Assessment of publication bias

Publication bias was assessed in accordance to the recommendations from the Cochrane Handbook for Systematic Reviews of Intervention (Higgins et al., 2011). Funnel plots were used for the assessment if there were more than 10 studies contributed to the outcome (Guyatt et al., 2015; Higgins et al., 2011).

Assessment of quality of evidence

The quality of evidence for each outcome was evaluated independently by adopting the Grading of Recommendations Assessment Development and Evaluation (GRADE) approach (Ryan & Hill, 2016). Although the quality of evidence began as low since only observational studies were included, the body of evidence was subject to further downgrading when the body of evidence was presented with serious issues related to risk of bias, imprecision, inconsistency, indirectness, and publication bias, or being upgraded due to large magnitude of effect, dose response, or no plausible confounding.

Results

Study selection

A systematic literature search yielded 1437 records, 1192 records remained after removal of duplicates. A total of 58 articles were retrieved and scrutinized for full-text reading, which 42 studies were excluded with the following reasons: no non-ASD controls (n = 14), irrelevant articles (n = 10), no English full-text retrievable (n = 5), adults diagnosed with ASD (n = 5), other disabilities as control (n = 4), review articles (n = 3), and survey without examination (n = 1). Sixteen case-control studies met the inclusion criteria and were included for qualitative syntheses (kappa = 0.885). For quantitative synthesis, only 15 studies were included as data from one study were not comparable. Figure 1 presents the study identification and screening process following the MOOSE flowchart, and Supplemental Material, Appendix 2 reports the reasons for exclusion after full-text reading when determining final eligibility.

Figure 1.

Flowchart of screening process.

Study characteristics

The characteristics of the 14 prospective and 2 retrospective case-control studies are summarized in Table 1. A total of 2691 subjects from 11 countries across Asia, Europe, and North and South America were included, which 1244 children and adolescents diagnosed with ASD were compared to 1447 individuals without ASD. Most studies recruited their autistic participants from special needs schools or centers (87.5%) and hospitals (12.5%), while controls were selected from “regular” schools (43.75%), dental or medical clinics (31.25%), hospitals (6.25%), or recruited siblings, relatives, and friends (18.75%). Approximately one-third (31.25%) of the studies only enrolled subjects and controls without other medically compromised conditions, while around one-third (31.25%) of the studies excluded autistic participants, who were extremely aggressive and uncooperative for examination. More than two-thirds of the included studies reported recruiting controls of similar socioeconomic backgrounds (62.5%), age (81.25%), and genders (62.5%).

Table 1.

Characteristics of included studies.

Study (year, country^a)	Study design	Number of subjects (% males)		Age range (year)	Recruitment	Inclusion (I)/Exclusion (E) criteria	Control matching	Outcome measures
Bhandary and Hari (2017; IND)	Prospective	ASD	30 (66.7)	6–12	Special needs schools and hospitals	(I)Diagnosed as ASD by neurologist (E) Extremely aggressive^b (E) With underlying medically compromised conditions^c (E) healthy siblings with underlying medical conditions	 Socioeconomic  Age X Gender	 Dental caries severity  Oral hygiene and periodontal status  Unstimulated salivary mean pH, flow rate, and buffering capacity  Dental trauma prevalence
		non-ASD	30 (26.7)	6–12	Aged-matched siblings
Fontaine-Sylvestre et al. (2017; CAN)	Retrospective	ASD	99 (78.8)	5–18	Children hospital dental division	(I) Confirmed medical diagnosis of ASD (E) Patients in mixed or permanent dentition (E) Previous orthodontic treatment (E) Another disorder or syndrome^c	 Socioeconomic  Age  Gender	 Malocclusion prevalence
		non-ASD	101 (82.2)	5–18	Children hospital dental division
Andrade et al. (2016; BRA)	Retrospective	ASD	114 (85.1)	6–12	Special needs public school and referral center	(I) Patients with ASD (E) Record lacking phone contact	 Socioeconomic  Age  Gender	 Dental traumatic injuries prevalence
		non-ASD	114 (85.1)	6–12	Dental clinic
Diab et al. (2016; SAU)	Prospective	ASD	50 (74)	4–15	Special needs school	(I) Diagnosis of autism with or without learning disability (E) Potentially uncooperative patients^b (E) Dental prophylaxis in the last 6 months (E) Patient with systemic disorder that affect periodontal disease and diabetes^c	X Socioeconomic  Age  Gender	 Oral hygiene and periodontal status  Unstimulated salivary pH and buffering capacity
		non-ASD	50 (74)	4–15	Outpatient clinic
Habibe et al. (2016; BRA)	Prospective	ASD	61 (80.3)	6–12	Special needs school	(I) Medical diagnosis of ASD (E) Behavior proved to be inadequate for clinical evaluation^b	 Socioeconomic  Age  Gender	 Dental trauma prevalence
		non-ASD	61 (80.3)	6–12	Dental and medical clinics
Sarnat et al. (2016; ISR)	Prospective	ASD	47 (83)	6–12	Special kindergartens	(I) Diagnosed as ASD	X Socioeconomic  Age X Gender	 Dental caries prevalence  Oral hygiene and periodontal status
		non-ASD	44 (22.7)	6–12	Normal kindergartens
Du et al. (2015; HKG)	Prospective	ASD	257 (84.4)	6–12	Special child care centers	(I) Children with ASD (E) Difficulty in conducting an oral health assessment^b	X Socioeconomic  Age  Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status  Bruxism prevalence  Dental trauma prevalence  Malocclusion
		non-ASD	257 (84.4)	6–12	Mainstream preschools
Fakroon et al. (2015; LBY)	Prospective	ASD	50 (80)	6–12	Center of autism	(I) Diagnosis of ASD (E) Extremely uncooperative^b (E) Diagnosed for any other illness that could have an effect on occurrence of dental caries^c	 Socioeconomic  Age  Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status
		non-ASD	50 (80)	6–12	Schools from the same location
Study (year, country^a)	Study design	Number of subjects (% males)		Age range (year)	Recruitment	Inclusion (I)/Exclusion (E) criteria	Control matching	Outcome measures
El Khatib et al. (2014; EGY)	Prospective	ASD	100 (75)	6–12	Government and private institutions of intellectually disabled children	(I) Diagnosed with ASD (DSM-IV-TR)	 Socioeconomic  Age  Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status  Bruxism prevalence
		non-ASD	100 (73)	6–12	Government and private school
Richa et al. (2014; IND)	Prospective	ASD	135 (80)	6–12	Special schools	(I) Diagnosis of autism (based on records) (E) Prophylaxis in the last 6 months (E) Suffer from other diseases known to influence dental caries or the severity of periodontal disease^c	X Socioeconomic X Age X Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status  Bruxism prevalence
		non-ASD	135 (58.5)	6–12	Regular schools
Rai et al. (2012; IND)	Prospective	ASD	101 (NR)	6–12	Special schools	(I) Children with Autism	 Socioeconomic  Age X Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status  Unstimulated salivary median pH and buffering capacity
		non-ASD	50 (NR)	6–12	Normal healthy siblings
Jaber (2011; ARE)	Prospective	ASD	61 (73.4)	6–16	Autism centers	(I) Children diagnosed with Autism	 Socioeconomic  Age  Gender	 Dental caries prevalence and severity  Oral hygiene and periodontal status
		non-ASD	61 (73.4)	6–16	Normal healthy relatives or friends
Luppanapornlarpet al. (2010; THA)	Prospective	ASD	32 (78.1)	8–12	(NR)	(I) Diagnosed autism (E) Inability to cooperate in oral examination^b	X Socioeconomic X Age X Gender	 Oral hygiene and periodontal status  Malocclusion prevalence
		non-ASD	48 (39.5)	8–12	Average children of the pediatric clinic
Bassoukou et al. (2009; BRA)	Prospective	ASD	25 (100)	6–12	Day-care autism centers	(I) Medical diagnosis of autism	 Socioeconomic  Age  Gender	 Dental caries prevalence and severity  Unstimulated salivary mean flow rate, pH and buffering capacity
		non-ASD	25 (100)	6–12	University pediatric dental clinic
Namal et al. (2007; TUR)	Prospective	ASD	62 (74.2)	6–12	Autistic child center and elementary schools offering private classes to autistic children	(I) Autistic children	X Socioeconomic X Age X Gender	 Dental caries prevalence and severity
		non-ASD	301 (45.2)	6–12			Three elementary schools
Fahlvik-Planefeldt and Herrstrom (2001; SWE)	Prospective	ASD	20 (60)	4–17	Psychiatric outpatients ward	(I) Individual with an autistic disorder	 Socioeconomic  Age  Gender	 Dental caries prevalence  Periodontal status: prevalence of gingivitis
		non-ASD	20 (60)	4–17	Regular dental clinic

ASD: Autism Spectrum Disorders; DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.); NR: Not reported.

ISO alpha-3 codes of countries. ^b Excluding ASD children and adolescents who are uncooperative for examination. ^c Excluding ASD and non-ASD children and adolescents with underlying medical conditions.

Risk of bias of included studies

Using the Sterne et al. (2016) ROBINS-I tool, the risk of bias of each included study was evaluated and reported in Figure 2. All studies were assessed as of low risk of bias in domain III classification of interventions and domain IV deviations from the intended interventions, as they included only subjects with a clear and confirmed diagnosed of ASD. All studies were also rated as of low risk of bias in domain V bias due to missing data and domain VII bias in selection of reported results, with no significant deviation of outcome measurements were detected.

Figure 2.

Assessment of risks of bias using ROBINS-I tool.

Six studies (Diab et al., 2016; Du et al., 2015; Luppanapornlarp et al., 2010; Namal et al., 2007; Richa et al., 2014; Sarnat et al., 2016) were graded as serious risk of bias in domain I “bias due to confounding,” as they lacked matching of individuals diagnosed with ASD with controls of similar age, gender, socioeconomic background, or a combination thereof. Since a large proportion of individuals diagnosed with ASD may have other systemic disorders, which are potential confounders to the results, studies with unclear reporting of both case and control subjects’ underlying medical conditions were judged as of moderate risk of bias. Only three studies (Bhandary & Hari, 2017; Fakroon et al., 2015; Fontaine-Sylvestre et al., 2017) were graded as having a low risk of bias as they specifically included all case and control subjects without other underlying medically compromised conditions which may be associated with oral diseases.

In domain II “bias in selection of participants into the study,” five studies (Bassoukou et al., 2009; Diab et al., 2016; Fahlvik-Planefeldt & Herrstrom, 2001; Habibe et al., 2016; Luppanapornlarp et al., 2010) were graded as high risk of bias as they recruited healthy controls from dental clinics compared with autistic participants from schools or non-dental facilities. Since a higher proportion of patients seeking dental treatments may have established dental problems compared to the general population, these confounders are closely associated with poorer outcomes. Four studies (Bhandary & Hari, 2017; Du et al., 2015; Fakroon et al., 2015; Rai et al., 2012) were rated of moderate risk of bias as they excluded autistic participants who displayed aggressive or uncooperative behaviors, which may be related to the oral hygiene practice and access to preventive dental care, and thus affecting the outcomes. Studies which demonstrated specific behavioral techniques and performed dental examinations on all eligible autistic individuals were judged as of low risk of bias in this domain.

In domain VI bias in measurement of outcomes, blinding of outcome assessors could not be achieved in studies which dental examinations were conducted separately in special needs and regular schools or kindergartens, respectively. Therefore, nine studies (Bassoukou et al., 2009; Diab et al., 2016; Du et al., 2015; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Fakroon et al., 2015; Habibe et al., 2016; Richa et al., 2014; Sarnat et al., 2016) were rated as of high risk of bias. Seven studies (Andrade et al., 2016; Bhandary & Hari, 2017; Fontaine-Sylvestre et al., 2017; Jaber, 2011; Luppanapornlarp et al., 2010; Namal et al., 2007; Rai et al., 2012) were graded as of moderate risk of bias as they performed assessment on matched siblings, friends, or other controls in the same settings, although outcome assessors may identify autistic participants depending on the disorder severity.

Based on the tool guidelines, five studies (Andrade et al., 2016; Bhandary & Hari, 2017; Fontaine-Sylvestre et al., 2017; Jaber, 2011; Rai et al., 2012) have at least one domain graded as having moderate risk of bias, therefore, being considered as moderate risk of overall bias. Eleven studies (Bassoukou et al., 2009; Diab et al., 2016; Du et al., 2015; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Fakroon et al., 2015; Habibe et al., 2016; Luppanapornlarp et al., 2010; Namal et al., 2007; Richa et al., 2014; Sarnat et al., 2016) had no less than one domain determined as high risk of bias; hence, they were classified as of serious risk of overall bias.

Dental caries experience

Summarized in Table 2, 11 studies (Bassoukou et al., 2009; Bhandary & Hari, 2017; Du et al., 2015; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Fakroon et al., 2015; Jaber, 2011; Namal et al., 2007; Rai et al., 2012; Richa et al., 2014; Sarnat et al., 2016) with a total of 1961 case-control subjects had reported outcomes regarding dental caries experience in terms of caries prevalence (i.e. decayed missing filled teeth or surfaces (DMFT/dmft/DMFS/dmfs) > 0) and caries severity (i.e. mean and median DMFT/dmft/DMFS/dmfs) or a combination thereof (Oliveira et al., 1998).

Table 2.

Comparison of caries prevalence and severity between ASD and non-ASD children and adolescents.

Study (year)	Number of subjects		Outcomes
	ASD	Non-ASD	Caries prevalence			Caries severity			Untreated caries severity
	ASD	Non-ASD		OR	95% CI		SMD	95% CI		SMD	95% CI
1. Bhandary and Hari (2017)	30	30		(NR)		dmft	0.39	(–0.12, 0.90)	DT	0.29	(–0.22, 0.80)
1. Bhandary and Hari (2017)						DMFT	0.57	(0.05, 1.09)	dt	0.42	(–0.09, 0.94)
2. Sarnat et al. (2016)	47	44	dmft > 0	0.43	(0.18, 1.00)	dmft	–0.23	(–0.34, 0.94)
3. Du et al. (2015)	257	25	dmft > 0	0.53	(0.37, 0.75)*↓	dmfs	–0.18	(–0.36, –0.01)*↓	ds	–0.18	(–0.36, –0.01)*↓
4. Fakroon et al. (2015)	50	50		(NR)		dmft	–0.64	(–1.04, –0.24)*↓	DT	–0.62	(–1.02, –0.22)*↓
4. Fakroon et al. (2015)						DMFT	–4.67	(–5.43, –3.91)	dt	0.41	(0.01, 0.81)*↑
5. El Khatib et al. (2014)	100	100	dmft > 0	0.65	(0.22, 1.92)	dmft	–0.01	(–0.53, 0.51)	dt	–0.31	(–0.83, 0.21)
5. El Khatib et al. (2014)			DMFT > 0	0.50	(0.15, 1.68)	DMFT	–0.02	(–0.59, 0.55)
6. Richa et al. (2014)	135	135		(NR)		dmft	0.49	(0.25, 0.74)*↑		(NR)
						DMFT	0.23	(–0.04, 0.49)
						DMFS	0.3	(0.01, 0.60)*↑
7. Rai et al. (2012)	101	50		(NR)			(NR)			(NR)
8. Jaber (2011)	61	61	DMFT/dmft > 0	3.96	(1.81, 8.64)*↑	dmft	1.96	(1.53, 2.39)		(NR)
8. Jaber (2011)						DMFT	2.01	(1.58, 2.45)*↑
9. Bassoukou et al. (2009)	25	25		(NR)		dmft	–0.03	(–1.52, 1.47)		(NR)
9. Bassoukou et al. (2009)						DMFT	0.14	(–1.52, 1.03)
10. Namal et al. (2007)	62	301	DMFT > 0	0.51	(0.29, 0.90)*↓		(NR)			(NR)
11. Fahlvik-Planefeldt and Herrstrom (2001)	20	20	DMFT/dmft > 0	0.43	(0.12, 1.57)		(NR)			(NR)

ASD: autism spectrum disorder; dmft/DMFT: decayed, missing, filled teeth for primary/permanent dentition; DMFS/dmfs: decayed, missing, filled tooth surface for primary/permanent dentition; dt/DT: untreated decayed teeth for primary/permanent dentition; ds/DS: untreated decayed tooth surfaces for primary/permanent dentition; NR: not reported; OR: odds ratio; SMD: standardized mean difference; CI: confidence interval.

*↑

: Significantly higher.

*↓

: Significantly lower.

Caries prevalence were evaluated in six studies (Du et al., 2015; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Jaber, 2011; Namal et al., 2007; Sarnat et al., 2016). Two studies (Du et al., 2015; Namal et al., 2007) reported significantly lower caries prevalence among individuals diagnosed with ASD; while one study (Jaber et al., 2011) found otherwise; the remaining four studies found no significant difference between the two groups (El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Namal et al., 2007; Sarnat et al., 2016).

Results for caries severity were also inconsistent. Six studies (Bassoukou et al., 2009; Bhandary & Hari, 2017; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001; Namal et al., 2007; Sarnat et al., 2016) found no significant difference, two studies found significantly lower mean dmft/dmfs (Du et al., 2015; Fakroon et al., 2015), and two studies reported significantly higher mean dmft/DMFS/DMFT among individuals diagnosed with ASD (Jaber et al., 2011; Richa et al., 2014).

Five studies (Bhandary & Hari, 2017; Du et al., 2015; El Khatib et al., 2014; Fakroon et al., 2015; Sarnat et al., 2016) investigated the untreated decay prevalence among the two groups, which three studies found no significant difference (El Khatib et al., 2014; Sarnat et al., 2016), one study reported significantly higher prevalence of untreated decay in primary dentition but lower in permanent dentition (Fakroon et al., 2015), and one study found significantly lower prevalence in primary dentition (Du et al., 2015).

Meta-analysis revealed a significantly lower proportion of children and adolescents diagnosed with ASD had dental caries in subgroup analyses of primary dentition (OR = 0.52; 95% CI = 0.38, 0.72; I² = 0.0%, p = 0.829) and permanent dentition (OR = 0.51; 95% CI = 0.30, 0.85; I² = 0.0%, p = 0.977) (Figure 3(a) in Supplemental Material, Appendix 3); however, no statistical significant difference with considerable heterogeneity was found in overall caries prevalence (OR = 0.69; 95% CI = 0.39, 1.23; I² = 75.0%, p = 0.001) (Figure 3(a) in Supplemental Material, Appendix 3), mean caries experience (SMD = 0.04; 95% CI = –0.48, 0.57; I² = 96.1%, p < 0.001) (Figure 4(a) in Supplemental Material, Appendix 3), or mean untreated caries experience (SMD = –0.02; 95% CI = –0.34, 0.30; I² = 75.7%, p = 0.001) (Figure 5 in Supplemental Material, Appendix 3).

As half of the studies included were rated as high risk of selection bias, rather than performing sensitivity analyses, a further exploratory subgroup analysis grouping the studies with and without matched controls of similar socioeconomic backgrounds was performed (Figure 3(b) in Supplemental Material, Appendix 3). Significantly lower caries prevalence with minimal heterogeneity was found only in subgroup analysis of those studies without matching of socioeconomic background and high serious risks of bias (OR = 0.51; 95% CI = 0.39, 0.68; I² = 0.0%, p = 0.905), but not in the subgroup analysis of those studies with matched controls (OR = 1.04; 95% CI = 0.25, 4.42; I² = 86.2%, p = 0.001).

As most of the studies included in the meta-analysis of caries severity were of overall high risk of bias, sensitivity analyses were conducted to determine whether the effect estimate is dependent of any studies with low internal validity. The results of sensitivity analyses of mean dmft/DMFT also indicated that the effect estimate being significantly influenced by one study (Fakroon et al., 2015), which the effect estimate shifted from no difference to a lower mean, respectively (SMD = 0.48; 95% CI = 0.06, 0.89; I² = 93.1%, p < 0.001) (Figure 4(b) in Supplemental Material, Appendix 3).

Begg’s and Egger’s funnel plots were used to assess the potential publication bias of caries prevalence, since more than 10 studies reporting such outcome were identified. The publication bias was rated as of not serious in both Begg’s (Figure 4(c) in Supplemental Material, Appendix 3) and Egger’s test (Figure 4(d) in Supplemental Material, Appendix 3).

The body of evidence comparing caries prevalence, caries severity, and untreated caries prevalence were all assessed as of very low quality in accordance to the GRADE assessment criteria: due to observational data, overall high risk of bias, and considerable inconsistency (Table 5).

Oral hygiene and periodontal status

Nine studies (1313 subjects) evaluated the oral hygiene and periodontal status of individuals diagnosed with and without ASD with different parameters (Bassoukou et al., 2009; Bhandary & Hari, 2017; Diab et al., 2016; Du et al., 2015; El Khatib et al., 2014; Fakroon et al., 2015; Jaber, 2011; Luppanapornlarp et al., 2010; Sarnat et al., 2016), including simplified oral hygiene index (OHI-S; Greene & Vermillion, 1964), community periodontal index of treatment needs (CPITN; Cutress et al., 1987), prevalence of gingival bleeding, plaque index, and gingival index (Löe, 1967) (Table 3; Figures 6(a) and 7(a) in Supplemental Material, Appendix 3).

Table 3.

Comparison of oral hygiene and periodontal status between ASD and non-ASD children and adolescents.

Study (year)	Number of subjects		Outcomes
	ASD	Non-ASD	Inadequate oral hygiene						Gum bleeding						Calculus and periodontal pockets
	ASD	Non-ASD		OR	95% CI		WMD	95% CI		OR	95% CI		WMD	95% CI		OR	95% CI
1. Bhandary and Hari (2017)	30	30	OHI-S (M&P)	3.05	(1.05, 8.84)*↑				MGI	3.14	(1.07, 9.27)*↑					(NR)
2. Diab et al. (2016)	50	50				PI	0.48	(0.33, 0.64)*↑				GI	0.47	(0.17, 0.77)		(NR)
3. Sarnat et al. (2016)	47	44	OHI-S (M&P)	0.71	(0.26, 1.97)											(NR)
4. Du et al. (2015)	257	257				PI	–0.15	(–0.19, 0.11)*↓	MGI	0.58	(0.41, 0.83)*↓	GI	–0.14	(–0.19, –0.09)		(NR)
5. Fakroon et al. (2015)	50	50	CPITN > 0	7.19	(2.48, 20.83)*↑										CPITN > 1	1.95	(0.91, 4.19)
6. El Khatib et al. (2014)	100	100				PI	0.62	(0.41, 0.83)*↑				GI	0.6	(0.39, 0.81)
7. Luppanapornlarp et al. (2010)	32	48	CPITN > 0	3.98	(1.04, 15.23)*↑				MGI	3.98	(1.04, 15.23)*↑				CPITN > 1	3.98	(0.93, 11.52)
8. Jaber (2011)	61	61	OHI-S (M&P)	42.48	(9.49, 190.14)*↑				MGI	42.48	(9.49, 190.14)*↑
9. Fahlvik-Planefeldt and Herrstrom (2001)	20	20			(NR)				MGI	1.23	(0.35, 4.31)

ASD: Autism Spectrum Disorder; CPITN: community periodontal index of treatment need; GI: gingival index; MGI: Marginal gingival inflammation; NR: Not reported; OHI-S (M&P): Simplified Oral Hygiene Index (moderate and poor grading); PI: plaque index; OR: odds ratio; WMD: Weighted mean difference; CI: confidence interval.

*↑

: Significantly higher among ASD children and adolescents.

*↓

: Significantly lower among ASD children and adolescents.

Regarding oral hygiene status, five studies evaluated this outcome either using the OHI-S, CPITN (Bhandary & Hari, 2017; Fakroon et al., 2015; Jaber et al., 2011; Luppanapornlarp et al., 2010; Sarnat et al., 2016), or plaque index (Diab et al., 2016; Du et al., 2015; El Khatib et al., 2014). Seven out of eight studies (Bhandary & Hari, 2017; Diab et al., 2016; El Khatib et al., 2014; Fakroon et al., 2015; Jaber et al., 2011; Luppanapornlarp et al., 2010; Sarnat et al., 2016) found that a significantly higher proportion of children and adolescents diagnosed with ASD had inadequate oral hygiene. However, the same results only obtained in the meta-analysis of CPITN (OR = 5.72; 95% CI = 2.49, 13.17; I² = 61.4%, p = 0.108), but not in OHI-S (OHI-S medium/poor: OR = 4.24; 95% CI = 0.51, 35.40; I² = 89.9%, p < 0.001; OHI-S poor: OR = 4.04; 95% CI = 0.78, 20.83; I² = 71.5%, p = 0.061) and plaque index (WMD = 0.31; 95% CI = –0.23, 0.85; I² = 98.0%, p = 0.001).

No significant difference was identified in periodontal status between the two groups. Although five out of seven studies (Bhandary & Hari, 2017; Diab et al., 2016; El Khatib et al., 2014; Fakroon et al., 2015; Luppanapornlarp et al., 2010) revealed significant increase in gum bleeding among individuals diagnosed with ASD, meta-analysis showed no significant difference in terms of prevalence of gingival bleeding (OR = 3.01; 95% CI = 0.72, 12.51; I² = 90.3%, p < 0.001) (Figure 6(a) in Supplemental Material, Appendix 3), gingival index (GI: WMD = 0.30; 95% CI = –0.26, 0.86; I² = 96.9%, p < 0.001) (Figure 7 in Supplemental Material, Appendix 3), and prevalence of calculus and periodontal pockets (CPITN > 1; OR = 3.28; 95% CI = 0.93, 11.52; I² = 61.4%, p = 0.108) (Figure 6(a) in Supplemental Material, Appendix 3).

After conducting sensitivity analysis, the study of Du et al. (2015) with no matched controls significantly deviated from the others. Increased prevalence of gingival bleeding, gingival index, and plaque among individuals diagnosed with ASD with reduced inconsistency were found in meta-analysis when the study was omitted from the meta-analysis (prevalence of gingival bleeding: OR = 4.80; 95% CI = 1.25, 18.36; I² = 77.1%, p = 0.004 (Figure 6(b) in Supplemental Material, Appendix 3); GI: WMD = 0.56; 95% CI = 0.38, 0.73; I² = 0.0%, p = 0.478; PI: WMD = 0.53; 95% CI = 0.41, 0.66; I² = 4.9% (Figure 7(b) in Supplemental Material, Appendix 3)). Due to observational data, the overall high risk of bias, and considerable heterogeneity, the quality of evidence for comparing gingivitis prevalence was rated as of very low quality. Therefore, the effect estimate of both outcomes is uncertain (Table 5).

Malocclusion

Four studies (Bassoukou et al., 2009; Du et al., 2015; Fontaine-Sylvestre et al., 2017; Luppanapornlarp et al., 2010) reported the prevalence of malocclusion of 834 children and adolescents diagnosed with and without ASD. An exploratory meta-analysis revealed no statistical significant differences between the two groups in terms of prevalence of malocclusion (OR = 1.62; 95% CI = 0.68, 3.84; I² = 63.8%, p = 0.063), and in subgroup analysis of prevalence of anterior open bite (OR = 1.40; 95% CI = 0.40, 4.84; I² = 51.2%, p = 0.129), deep overbite (OR = 1.16; 95% CI = 0.78, 1.74; I² = 15.2%, p = 0.278), class II molar relationship (OR = 1.45; 95% CI = 0.88, 2.37; I² = 0.0%, p = 0.882), increased overjet (OR = 1.40; 95% CI = 0.56, 3.45; I² = 79.8%, p = 0.007), dental crowding (OR = 0.59; 95% CI = 0.17, 2.03; I² = 77.1%, p = 0.037), anterior crossbites (OR = 1.37; 95% CI = 0.85, 2.20; I² = 0.0%, p = 0.816), and posterior crossbites (OR = 1.70; 95% CI = 0.27, 10.62; I² = 36.7%, p = 0.209) (Table 4 and Figure 8 in Supplemental Material, Appendix 3).

Table 4.

Comparison of malocclusion prevalence, dental traumatic Injury, Bruxism, salivary flow rate, and pH.

Study (year)	Age	Outcome
		ASD	Non-ASD	Malocclusion		Dental Traumatic Injury		Bruxism		Salivary Flow Rate		Salivary pH
		ASD	Non-ASD	OR	95% CI	OR	95% CI	OR	95% CI	WMD	95% CI	WMD	95% CI
Bhandary and Hari (2017)	6–12	30	30		(NR)	2.15	(0.36, 12.76)		(NR)	0.02	(–0.19, 0.23)	–0.59	(–0.89, –0.29)*↓
Fontaine-Sylvestre et al. (2017)	5–18	99	101	2.55	(1.44, 4.52)*↑		(NR)		(NR)		(NR)		(NR)
Andrade et al. (2016)	3–15	114	114		(NR)	0.46	(0.26, 0.82)*↓		(NR)		(NR)		(NR)
Habibe et al. (2016)	4–17	61	61		(NR)	1.32	(0.77, 10.04)		(NR)		(NR)		(NR)
Diab et al. (2016)	4–15	50	50		(NR)		(NR)		(NR)		(NR)	–0.23	(–0.43, –0.04)*↓
Du et al. (2015)	2.5–7	257	257		(NR)	1.1	(0.72, 1.67)	1.26	(0.89, 1.79)		(NR)		(NR)
El Khatib et al. (2014)	3–13	100	100		(NR)		(NR)	7.05	(3.08, 16.13)*↑		(NR)		(NR)
Luppanapornlarp et al. (2010)	8–12	32	48	0.69	(0.27, 1.77)		(NR)		(NR)		(NR)		(NR)
Bassoukou et al. (2009)	3–8	10	14		(NR)		(NR)		(NR)	0.07	(–0.22, 0.36)	–0.10	(–0.42, 0.22)
	9–13	15	11						(NR)	–0.18	(–0.50, 0.14)	–0.33	(–0.53, –0.14)*↓
Fahlvik-Planefeldt and Herrstrom (2001)	4–17	20	20	1.62	(0.68, 3.84)		(NR)	0.46	(0.11, 2.19)		(NR)		(NR)

ASD: autism spectrum disorder; NR: not reported; OR: odds ratio; WMD: weighted mean difference; CI: confidence interval.

*↑

: Significantly higher among ASD children and adolescents.

*↓

: Significantly lower among ASD children and adolescents.

In the GRADE assessment, the quality of evidence was downgraded twice to very low due to overall serious risk of bias and substantial inconsistency (Table 5).

Table 5.

GRADE summary of findings table for the primary outcome (caries prevention and arrest) and secondary outcome.

Outcome	Comparison	No. of studies	No. of ASD and non-ASD individuals	Results	Risk of bias^a	Inconsistency^b		Indirectness^c	Imprecision^d	Publication bias^e	Quality of evidence (GRADE)
Outcome	Comparison	No. of studies	No. of ASD and non-ASD individuals	Results	Risk of bias^a	I² statistics	Heterogeneityχ² test (p value)	Indirectness^c	Imprecision^d	Publication bias^e	Quality of evidence (GRADE)
Caries experience	Caries prevalence	8	504 and 731	No significant difference	Serious	75.0%*	0.001**	Not serious	Not serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and substantial inconsistency
	Caries prevalence				↓	↓	–	–	–
	Caries severity	11	705 and 702	No significant difference	Serious	95.6%*	<0.001**	Not serious	Not serious	Not serious	⊕OOO very low due to observational data, serious risk of overall bias and substantial inconsistency
	Caries severity				↓	↓		–	–	–
	Untreated caries prevalence	5	447 and 444	No significant difference	Serious	75.7%*	0.001**	Not serious	Not serious	NA	⊕OOO very low due to observational data, serious risk of overall bias, and substantial inconsistency
					↓	↓		–	–	–
Periodontal condition	Oral hygiene	7	169 and 229^#	Significantly poorer oral hygiene among ASD individuals	Serious	86.9%*	<0.001**	Not serious	Serious	NA	⊕OOO very low due to observational data, serious risk of overall bias, substantial inconsistency and imprecision
	Oral hygiene			Significantly poorer oral hygiene among ASD individuals	↓	↓		–	↓	–
	Gingivitis	5	400 and 416	No significant difference	Serious	90.3%*	<0.001**	Not serious	Not serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and substantial inconsistency
	Gingivitis			No significant difference	↓	↓		–	–	–
Malocclusion	Malocclusion prevalence	5	151 and 169^#	No significant difference	Serious	63.8%	0.063	Not serious	Serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and imprecision
Malocclusion	Malocclusion prevalence			No significant difference	↓	–		–	↓	–
Dental traumatic injuries (DTI)	DTI prevalence	4	421 and 421	No significant difference	Serious	70.0%*	0.019**	Not serious	Not serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and substantial inconsistency
Dental traumatic injuries (DTI)	DTI prevalence			No significant difference	↓	↓		–	–	–
Bruxism	Bruxism prevalence	3	337 and 337	Inconsistent results	Serious	88.3%*	<0.001**	Not serious	Not serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and substantial inconsistency
Bruxism	Bruxism prevalence			Inconsistent results	↓	↓		–	–	–
Salivary flow rate and pH	Unstimulated salivary flow rate	2	55 and 55^#	No significant difference	Serious	0.0%	0.488	Not serious	Serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and imprecision
	Unstimulated salivary flow rate			No significant difference	↓	–		–	↓	–
	Salivary pH	3	105 and 105^#	Statistically but not clinically significantly lower pH among ASD individuals	Serious	52.6%	0.096	Not serious	Serious	NA	⊕OOO very low due to observational data, serious risk of overall bias and imprecision
	Salivary pH				↓	–		–	↓	–

ASD: Autism Spectrum Disorders; GRADE: Grading of Recommendations Assessment Development and Evaluation; CI: confidence interval; ↓: Downgrade by one level in quality of evidence; –: No change in quality of evidence.

Risk of bias: Considered as serious if overall half of the studies included were of serious risk of overall bias. ^b Inconsistency: Considered as serious when I² statistics ⩾70% (*) and p value of χ² test < 0.05 (**). ^c Indirectness: Considered as serious when applicability of findings were restricted in terms of population, intervention, comparator and outcomes. ^d Imprecision: Considered as serious when total number of events was below 300 for dichotomous outcomes or 400 for continuous outcomes (^#), or when the upper and lower limits of 95% CI include both meaningful benefits and harm. ^e Publications bias: Considered as serious if p value of Begg’s funnel plot <0.05. Not applicable (NA) if funnel plot could not be constricted given limited numbers of study. Publication bias was difficult to detect and thus no downgrading was performed.

Dental trauma injuries

The meta-analysis on the dental traumatic experience among children and adolescents with and without ASD (four studies with 842 subjects included; Andrade et al., 2016; Bhandary & Hari, 2017; Du et al., 2015; Habibe et al., 2016) identified no statistical significant differences (OR = 1.06; 95% CI = 0.51, 2.22; I² = 70.0%, p = 0.019). No significant differences were observed in subgroup analyses (two studies; Andrade et al., 2016; Habibe et al., 2016) in terms of males (292 boys; OR = 0.66; 95% CI = 0.18, 2.39; I² = 83.2%, p = 0.015) and females (58 girls; OR = 3.32; 95% CI = 0.54, 20.26; I² = 47.4%, p = 0.168) (Table 4 and Figure 9 in Supplemental Material, Appendix 3). Following the GRADE recommendation, the body of evidence was downgraded by two levels due to overall high risk of bias and substantial inconsistency, and thus evaluated as of very low quality (Table 5).

Bruxism

Three studies involving 754 subjects (Du et al., 2015; El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001) provided inconclusive results regarding the comparison of prevalence of bruxism among children diagnosed with and without ASD, with two studies (El Khatib et al., 2014; Fahlvik-Planefeldt & Herrstrom, 2001) identifying no significant difference and the other study (Du et al., 2015) reporting a higher prevalence of bruxism among children and adolescents diagnosed with ASD. Three meta-analysis identified an increased prevalence of bruxism among individuals diagnosed with ASD (OR = 1.62; 95% CI = 1.20, 2.19), the heterogeneity among the studies was substantial (I² = 88.3%, p < 0.001) (Table 4 and Figure 10 in Supplemental Material, Appendix 3). The estimate of effect is very uncertain due to overall serious risk of bias and considerable heterogeneity, with the quality of evidence evaluated being of very low quality (Table 5).

Salivary flow rate, pH, and buffering capacities

Two studies (Bassoukou et al., 2009; Bhandary & Hari, 2017; Fahlvik-Planefeldt & Herrstrom, 2001) assessed the mean unstimulated salivary flow rate of the two groups, with no significant difference found in both studies and also as per meta-analysis (WMD = –0.01; 95 CI = –0.16, 0.14; I² = 0.0%, p = 0.488) (Table 4 and Figure 11 in Supplemental Material, Appendix 3).

Three studies (Bassoukou et al., 2009; Bhandary & Hari, 2017; Diab et al., 2016) compared the mean unstimulated salivary pH of individuals diagnosed with ASD to the healthy controls (210 subjects). Children and adolescents diagnosed with ASD had a significant, but only slightly lower unstimulated salivary pH by 0.33 (95% CI = –0.53, –0.14; I² = 52.6%, p = 0.096) (Table 4 and Figure 12 in Supplemental Material, Appendix 3).

Two studies involving 110 subjects (Bassoukou et al., 2009; Bhandary & Hari, 2017) reported the mean salivary buffering capacities of both groups, but using different measurement and presentation methods. Using Ericsson’s method (Ericsson, 1959), Bhandary and Hari (2017) found that the mean buffering capacity of ASD group (4.28 ± 0.27) was significantly, but only slightly less than the control group (4.56 ± 0.27; p < 0.05). Bassoukou et al. (2009) determined the buffering capacity by titration method, performed subgroup analysis, and observed no significant difference among the children (aged between 3 and 8) diagnosed with and without ASD; the pH ranged from 4.0 to 7.0, while for children and adolescents aged 9–13, the group diagnosed with ASD were found to have a significantly lower buffering capacity (0.35 ± 0.25 mL acid/mL saliva) compared to the control group of similar age (0.74 ± 0.29 mL acid/mL saliva; p = 0.001) at pH above 7.0, but no significant difference at pH 6.9 or lower (p = 0.619). The heterogeneity of the effect estimate of both salivary flow rate and pH was not severe. Due to imprecision related to small sample size as well as overall high risk of bias of the included studies, the quality of evidence of both outcomes were rated as very low (Table 5).

Discussion

To warrant rigor and quality, the methodology of the review closely adapted the recommendation and guidelines suggested by the Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2011) and the MOOSE guidelines (Stroup et al., 2000). Multiple-study approach, including the use of both systematic literature view and meta-analysis, sensitivity meta-analyses, as well as systematical evaluation of the quality evidence adopting the GRADE approach (Guyatt et al., 2008) are all strengths of this review.

This review has also used the Risk of Bias in Non-randomized Studies of Intervention (ROBINS-I) tool (2016) (Sterne et al., 2016) to comprehensively assess the internal validity of all included studies, which was modified from Cochrane RoB tool for randomized trials (Higgins et al., 2011) and QUADAS 2 tool (Whiting et al., 2011) for evaluation of non-randomized studies. Other than evaluating “intervention,” an intentional “exposure,” many researchers have found the tool also applicable to assess effects of “unintentional exposure” (Losilla et al., 2018; Morgan et al., 2018). Most of the contents evaluated in ROBINS-I overlap with other assessment tools targeting observational studies like the Newcastle-Ottawa Scale (Morgan et al., 2018; Peterson et al., 2011), and are considered relevant and applicable for this review. The detailed algorithm offered by ROBINS-I gives minimal margin to rater’s decision and enhance inter-rater agreements (Losilla et al., 2018). Compared with other assessment tools for observational studies, for instance Newcastle-Ottawa Scale (Peterson et al., 2011), which were reported for relatively vague decision rules and underscoring bias results (Hartling et al., 2013; Stang, 2010), this tool allowed the review authors to perform the risk of bias assessment in a more systematic and evidence-based approach (Higgins et al., 2011), as well as resulting in lower inter-reviewer disagreement (Losilla et al., 2018). Since ROBINS-I is more demanding in the information reported in the articles, studies with poor study administration and reporting can be easily identified (Losilla et al., 2018). Quality of evidence in GRADE assessment can also be more easily compared as they are placed on a similar scale with randomized controlled trials when assessing risk of bias (Schünemann et al., 2018). In fact, a new tool ROBINS-E (Exposure) (Morgan, 2017) is under development by refining ROBINS-I to enhance users’ understanding and facilitate its application on exposure studies (Morgan et al., 2018). However, as ROBINS-E was still under modification and validation when this review was conducted (Morgan, 2017), ROBINS-I was chosen and used instead.

Multiple studies without English translated reports were inevitably excluded, but the influence of inclusion of non-English reports to the effect estimate might not be substantial as found in language restricted and language inclusive meta-analyses (Jüni et al., 2002; Moher et al., 2000). Studies which included adults (above 18 years old) diagnosed with ASD, whereas data of subjects below age 18 that could not be extracted for analysis were excluded. Funnel plots could only be used to assess publication bias in mean caries experience but not for other outcomes (Figure 3(c) and (d) in Supplemental Material, Appendix 3), due to the limited number of studies found.

Since ASD is a broad umbrella term covering individuals with different degree of mental conditions and functional abilities, the result validities of other outcomes may also be compromised by other confounders. This review has attempted to control potential confounders by demarcating the age, types of dentition, the degree of abilities of subjects included, and performing subgroup analyses; however, inadequate reporting and a limited number of studies found are the main constraints for precise subgroup analyses to be carried out. Many included studies excluded uncooperative individuals diagnosed with ASD who repudiated a dental examination, which may markedly affect study findings. Therefore, the evidence of most outcomes evaluated was of very low quality contributed by overall serious risks of bias of all observation studies included: inconsistencies and imprecisions.

The review included a representative sample aged between 4 and 18 years across 13 countries; however, the small sample sizes generated from the 16 studies preclude generalizability. High-quality studies with minimal risk of bias are lacking, possibly due to the difficulty in blinding outcome assessors and recruitment of matched controls.

Most participants fall in the age range of 6–12 years, which cover a spectrum from primary dentition to permanent dentition. To enable periodontal status, caries prevalence and severity to be compared, subgroup analyses of primary, mixed, and early permanent dentition have been performed. Although comparisons between adults diagnosed with ASD and their healthy controls are beyond the scope of this review, we encountered four studies that reported such findings during the screening process (Altun et al., 2010; Blomqvist et al., 2015; Loo et al., 2008; Orellana et al., 2012). The results reported in adult dentition are somewhat similar to the findings of this review, which significantly poorer oral hygiene among individuals diagnosed with ASD (Blomqvist et al., 2015; Orellana et al., 2012) and no significant differences in trauma prevalence (Altun et al., 2010) were identified. The findings of caries prevalence and severity are also similar, which individuals diagnosed with ASD were having either no difference or significantly lower caries prevalence and severity when age and socioeconomic status were not matched (Blomqvist et al., 2015; Loo et al., 2008; Orellana et al., 2012). The main differences from our current findings are more gingival recession and higher prevalence of anterior open bite was identified among adult individuals diagnosed with ASD (Blomqvist et al., 2015; Orellana et al., 2012). These results are not surprising as anterior open bite with genetic depositions and chronic periodontitis usually manifest from late maturation period to adulthood (Flemmig, 1999; Ngan & Fields, 1997). Therefore, the oral health status of adults diagnosed with ASD should be reviewed as a separate entity and further investigations are warranted.

The main question investigated by this review is whether the oral health status of children and adolescents diagnosed with ASD differs from those without. No significant differences were identified in terms of caries prevalence and severity, oral hygiene and periodontal status, prevalence of malocclusion and dental traumatic injuries, salivary flow rate, and buffering capacity below pH 6.9. Moreover, all estimates of effects were very uncertain due to divergent results and substantial heterogeneity as shown in meta-analyses and sensitivity analyses. There is very little confidence in the effect estimate as all studies included were judged to have moderate to high risk of bias, especially as many included studies did not match their controls with similar socio-demographic backgrounds, given the solid evidence that children and adolescents from lower socioeconomic groups experienced more caries (Arora et al., 2011; Kumar et al., 2016; Schwendicke et al., 2015). The majority of studies selected children as controls conveniently from dental clinics, and these children are likely to have a higher prevalence of oral diseases and increased carious risks compared with the general population (Goettems et al., 2012), as the reasons for dental visits among children were mostly problem-driven (Camargo et al., 2012). Hence, it is highly likely that the outcome results are contaminated with the effects of these confounders.

This review recognized the relatively lower resting salivary pH among individuals diagnosed with ASD and despite the limited studies, consistent results showed statistically significantly lower unstimulated salivary pH among individuals diagnosed with ASD. However, the results are not of clinical significance as an increased caries risk is reported to occur only when the resting salivary pH is below 6.0 (Cunha-Cruz et al., 2013).

Meta-analysis also revealed significant higher prevalence of bruxism among children and adolescents diagnosed with ASD, which might be associated with ASD-related comorbidities, for instance oro-mandibular dystonia and seizures (Ella et al., 2017); however, due to low internal validity and inconsistent results among the three included studies, valid conclusion could not be drawn and the body of evidence is of very low quality in this regard. Regrettably, there were also no eligible studies found to report tooth surface loss in relations to erosion, which was highly prevalent among children and adolescents in general (Corica & Caprioglio, 2014; Salas et al., 2015). The reported estimated prevalence of erosive tooth wear in permanent dentition was more than 30% (Salas et al., 2015), while that in primary dentition ranged from 5 to 35%, remarkably variant between different dietary patterns, age, and ethnic groups (Al-Malik et al., 2002; Corica & Caprioglio, 2014; Jones & Nunn, 1995; Luo et al., 2005). Autistic individuals might have an even higher prevalence of dental erosion, since gastrointestinal dysfunctions including gastroesophageal reflux and bloating are often reported by parents (Gorrindo et al., 2012; Kang et al., 2014), warranting further study and investigation.

Based on our current findings, the oral health status of children and adolescents diagnosed with ASD does not seem to differ significantly from their “typically developing” counterpart. Except for bruxism, the current evidence does not suggest that children and adolescents diagnosed with ASD are more prone to oral diseases such as dental caries, periodontal diseases, dental trauma, and malocclusion. The findings proposed that ASD itself might not be a predisposing factor to oral diseases; other risks factors, for instance, failure to maintain proper oral hygiene and an inclination to cariogenic diet, may play a more important role in its etiology. Therefore, medical and dental practitioners should make every effort to promote oral health and put forward oral disease prevention among individuals diagnosed with ASD and their caretakers. At the same time, stronger statements regarding the influence of ASD and other disease risk factors on individual’s oral health cannot be declared due to the dearth of high-quality evidence. This review thus calls for observational studies with better-matched controls and study administration, such that more concrete association between ASD and oral diseases can be established.

Conclusion

This review identified significantly higher prevalence of bruxism and lower resting salivary pH among children and adolescents diagnosed with ASD compared to those without ASD. No significant difference in terms of caries prevalence and severity, oral hygiene and periodontal status, prevalence of malocclusion, dental traumatic injuries, as well as salivary flow rate and buffering capacity between those diagnosed with and without ASD were observed. However, the quality of evidence of all outcomes was very low due to seriously low internal validity, considerable inconsistencies, and inclusion criteria of observational data. More high-quality case-control studies are warranted, so that a more descriptive and precise picture of the oral health status of ASD individuals can be drawn.

Supplemental Material

AUT877337_Supplemental_material_Appendix_1 – Supplemental material for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis

Supplemental material, AUT877337_Supplemental_material_Appendix_1 for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis by Phoebe PY Lam, Rennan Du, Simin Peng, Colman PJ McGrath and Cynthia KY Yiu in Autism

Supplemental Material

AUT877337_Supplemental_material_Appendix_2 – Supplemental material for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis

Supplemental material, AUT877337_Supplemental_material_Appendix_2 for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis by Phoebe PY Lam, Rennan Du, Simin Peng, Colman PJ McGrath and Cynthia KY Yiu in Autism

Supplemental Material

AUT877337_Supplemental_material_Appendix_3 – Supplemental material for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis

Supplemental material, AUT877337_Supplemental_material_Appendix_3 for Oral health status of children and adolescents with autism spectrum disorder: A systematic review of case-control studies and meta-analysis by Phoebe PY Lam, Rennan Du, Simin Peng, Colman PJ McGrath and Cynthia KY Yiu in Autism

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Rennan Du

Cynthia KY Yiu

Supplemental material

Supplemental material for this article is available online.

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