Racially minoritized children often bear a greater burden of dental caries, but the overall magnitude of racial gaps in oral health and their underlying factors are unknown. A systematic review and meta-analysis were conducted to fill these knowledge gaps. We compared racially minoritized (E) children aged 5–11 years (P) with same-age privileged groups (C) to determine the magnitude and correlates of racial inequities in dental caries (O) in observational studies (S). Using the PICOS selection criteria, a targeted search was performed from inception to December 1, 2021, in nine major electronic databases and an online web search for additional grey literature. The primary outcome measures were caries severity, as assessed by mean decayed, missing, and filled teeth (dmft) among children and untreated dental caries prevalence (d > 0%). The meta-analysis used the random-effects model to calculate standardized mean differences (SMD) and 95% confidence intervals (95% CI). Subgroup analysis, tests for heterogeneity (I2, Galbraith plot), leave-one-out sensitivity analysis, cumulative analysis, and publication bias (Egger’s test and funnel plots) tests were carried out. The New Castle Ottawa scale was used to assess risk of bias. This review was registered with PROSPERO, CRD42021282771. A total of 75 publications were included in the descriptive analysis. The SMD of dmft score was higher by 2.30 (95% CI: 0.45, 4.15), and the prevalence of untreated dental caries was 23% (95% CI: 16, 31) higher among racially minoritized children, compared to privileged groups. Cumulative analysis showed worsening caries outcomes for racially marginalized children over time and larger inequities in dmft among high-income countries. Our study highlights the high caries burden among minoritized children globally by estimating overall trends and comparing against factors including time, country, and world income. The large magnitude of these inequities, combined with empirical evidence on the oral health impacts of racism and other forms of oppression, reinforce that oral health equity can only be achieved with social and political changes at a global level.

Dental caries remains a major global public health problem, especially among socially disadvantaged school-aged children [Watt et al., 2019]. According to the Global Burden of Disease Study [Vos et al., 2016], dental caries is one of the most prevalent preventable non-communicable diseases worldwide, with an estimated 2.5 billion people affected and a 14.6% increase in dental caries over 10 years. Two recent literature reviews showed that the global prevalence of dental caries in primary teeth was 46.2%, and for permanent teeth, 53.8% [Kazeminia et al., 2020], with lower estimates observed in European and higher estimates in African [Frencken et al., 2017] countries.

Racially minoritized school-going children, particularly those from low-income families, including African Americans [Selvaraj et al., 2021], Hispanics [Matsuo et al., 2015], Indigenous or native populations [Grim et al., 1994; Nath et al., 2021b], have a higher dental caries prevalence than their white privileged counterparts. Racially minoritized children are defined as “individuals and populations, including numerical majorities, whose collective cultural, economic, political and social power has been eroded through the targeting of identity in active processes that sustain structures of hegemony” [Selvarajah et al., 2020]. Socially disadvantaged children are deprived of quality services and amenities that drive privileged children to have better living and health conditions [Cheng et al., 2016]. Some barriers include lack of access to fluoridated water and dental insurance, financial barriers to accessing preventive dental services, transportation issues, and limited availability of dental services and dentists in minority communities [Northridge et al., 2020]. The cultural and linguistic barriers make it harder for racially minoritized children to access dental care, and for them to navigate through the system [Jamieson et al., 2007a; Schwendicke et al., 2015; Henshaw et al., 2018]. Dental caries can negatively impact the physiological and psychological well-being of the affected child, their careers, and the broader community. Untreated dental caries in children can lead to severe pain and infection, interfering with their ability to eat, sleep, concentrate, and communicate. The social and emotional well-being of children experiencing pain due to untreated dental caries is also substantial [Mota-Veloso et al., 2016]. Racially minoritized children may experience early dental caries because of the cumulative stress imposed by peer pressure to conform to dominant cultural norms, exposure to marginalization and adversity, leading to disengagement from school, lower academic achievement and even develop behavioural or mental health problems [Forde et al., 2019; Park et al., 2022]. Frequent absenteeism due to dental pain or treatment can cause psychological stressors through segregation and stigmatization by peers at school [Rebelo et al., 2018; Ruff et al., 2019]. Decayed teeth can also impact children’s health, nutrition, growth, and body weight. For carers, the burden of treatment costs and loss of productivity and income due to work-related absenteeism is also considerable [Ruff et al., 2019].

Social forces, such as structural racism and governmental policies embracing neoliberalism, perpetuate these injustices over time [Bastos et al., 2018]. Structural racism is recognized as an upstream cause of poor dental health; it is essential also to examine its downstream effects, which are a cumulative result of institutional resources derived at the individual and community levels that promote dental health. Institutional racism is embedded and enforced in the dental health service system, policies and procedures create an environment favouring inequitable oral health outcomes due to decreased accessibility to school dental services or receiving poor quality dental care [Jamieson et al., 2021]. At an individual and community level, cultural racism can negatively impact oral health through racial discrimination and segregation, causing psychosocial stress and worsening oral health outcomes [Jamieson et al., 2021].

Racially minoritized children are considered vulnerable groups, and most countries have national public health policies, priorities, and social benefits to reduce the impact of these inequities towards the increasing chronic disease burden [Levine, 2021]. Despite these policies, dental caries among racially minoritized children is increasing [Vos et al., 2016; Peres et al., 2019; Watt et al., 2019]. To the best of our knowledge, assessing the inequities in dental caries among all racially minoritized children at a global level has yet to be undertaken. Previous research has focussed on country-specific race categorization or ethnicity [Alves Filho et al., 2014; Nath et al., 2021b], a particular geographical location [Zhang et al., 2015], or has been limited to a particular time frame [Bastos et al., 2021]. Estimating racial gaps in dental caries among school children would be a crucial step to develop targeted and culturally secure interventions for improving oral health and reducing inequities. Therefore, this systematic review and meta-analysis aim to: (1) quantify the magnitude of inequities of dental caries among racially minoritized children aged 5–11 years, compared to children from privileged or dominant groups of the same age by assessing the prevalence and severity of dental caries; (2) assess trends; and (3) identify correlates of racial gaps in dental caries. We propose that racial status is a proxy for the extent of exposure to systemic racism, therefore resulting in racial disparities in dental health outcomes.

Search Strategy and Selection Criteria

This systematic review and meta-analysis was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines [Page et al., 2021]. A detailed protocol of the methods has been published elsewhere [Nath et al., 2022]. The review was registered on PROSPERO (CRD42021282771) before the review commencement [Nath et al., 2021].

For this review, the population of interest was primary school-aged children between 5 and 11 years [Centers for Disease Control and Prevention, 2022] without any restriction for gender, geographic location, or language. Data were also included from national oral health surveys, country-based population studies, censuses, or government registries. To be included in the review, studies should meet the following inclusion criteria: (1) original research with either primary or secondary data, reporting dental caries as an outcome measure among racially minoritized children in the age group 5–11 years; (2) a national, majority, or privileged population children of similar age as a comparison group; and (3) clinical dental examination conducted for recording decayed, missing, and filled teeth in the primary dentition (dmft). For this review, we used the term “racially minoritized” as an umbrella description for a multitude of constructs, such as race, ethnicity, country-specific nationality, caste, religious groups, tribes, and linguistic groups. We excluded studies that reported race based on immigration status. Publications excluded from this review were case reports, case series, in vitro studies, and literature reviews.

The outcomes were the severity and prevalence of dental caries in the primary dentition. Severity was measured by considering the mean dmft and the prevalence of teeth with untreated caries as a percentage of d > 0. The severity and prevalence of dental caries were estimated with their standard deviation (SD) and 95% confidence interval (CI), respectively. Race indicated whether children belonged to racially marginalized or privileged groups in the reviewed studies. The taxonomic classification, the method of assessing race or ethnicity, the concepts used to categorize study participants according to race, and the meaning of race across studies were also recorded.

We performed a three-stage search strategy for this review. First, an initial electronic search was conducted in MEDLINE/PubMed to identify all potentially relevant articles from the platform’s inception until December 1, 2021. With the pilot search, all relevant terms (i.e., controlled vocabulary terms and text words) were identified, and the main search string was formed (online Table S1; for all online suppl. material, see https://doi.org/10.1159/000533565). In the second step, a total of nine electronic databases were searched using relevant terms, such as “ethnic,” “race,” “minoritized,” and “dental caries.” To include Indigenous populations, we used a similar strategy described previously [Nath et al., 2021a, 2022]. In the last step, additional eligible studies were identified by hand-searching the reference lists of review articles identified during the search and the final included articles. Similarly, a systematic approach to sourcing the grey literature was developed to identify all relevant websites for government reports, national oral health surveys, and government registries with comparative data on dental caries between race-based groups.

Data Extraction and Quality Assessment

All retrieved studies were uploaded into EndNote X9 and duplicates were removed. The remaining citations were transferred to the online systematic review management software, Covidence, where two independent researchers (SN & SS) screened the title, abstract, and full text of the selected studies following a data extraction form (online suppl. Table S2). The reasons for exclusion after the full-text assessment were recorded.

Information on study characteristics, participant characteristics, the definition of race, dental caries measurement, and the overall outcome of the study was extracted manually by both reviewers (SN & SS) independently. Several online tools and statistical methods were utilized to maximize data extraction and reduce publication bias (online suppl. Table S3). For articles in a language other than English, direct translation was done by co-authors who were native speakers in the language of the published article or via online translation tools such as Google Translate. For any missing information, the authors were directly contacted through email.

All included articles were read in full, and methodological quality was rated independently by two reviewers (SN & SS) using a modified version of the Newcastle Ottawa scale for prevalence studies [Wells et al., 2014]. Studies were scored as “very good” (9–10 points), “good” (7–8 points), “satisfactory” (5–6 points), and “unsatisfactory” (0–4 points). All studies were included in the review regardless of their quality. For the quality of evidence of outcomes, the standard Grading of Recommendations Assessment, Development and Evaluation (GRADE) was adopted, with scores ranging from 1 to 4, with one having low and four having a high degree of certainty [Murad et al., 2017].

Calibration between reviewers was achieved through overall agreement in each review step, using 10% of the included studies selected at random. Kappa values were calculated, and a score between 0.81 and 0.99 was considered acceptable. A third reviewer (LMJ) was consulted at any stage to resolve conflicts during disagreements between the two reviewers.

Data Synthesis

All the studies were subjected to qualitative analysis. For qualitative analysis, study characteristics, case and control groups description, and main outcomes related to caries prevalence and severity were recorded. Meta-analyses were conducted in Stata, version 17.0, statistical software (Stata Corporation, College Station, TX, USA). The meta-analysis was conducted for studies reporting mean and SD for the caries outcomes. The random-effects model with the restricted maximum likelihood method was used to calculate the standardized mean difference (SMD) and the corresponding 95% CI. Forest plots were constructed for visualization. The weighted average of study-specific effect sizes was estimated using Hedges’s g method. Racially minoritized children were considered cases, and the privileged group of children as controls. Both outcomes (mean dmft, d > 0%) were analysed separately. To observe changes over time, cumulative analyses showed how the overall estimate changes starting with a single study and adding the other studies one at a time to the timeline. Leave-one-out sensitivity analysis was carried out, which performs multiple meta-analyses by excluding one study at a time.

It was anticipated that effect sizes would have variations due to in-between study heterogeneity mainly from two sources: methodological and clinical outcome assessed. Different methods to assess and visualize heterogeneity were employed: (1) Forest plot, when there was a lack of overlap of the CIs; (2) Galbraith plots; and (3) I2 statistics estimated the percentage of between-study variability. To address heterogeneity, data were analysed according to two subgroups, i.e., country of study and world income index [World Bank, 2021].

Contour-enhanced (CE) funnel plots were constructed for both outcomes to discriminate bias due to publication versus other reasons [Egger et al., 1997]. The test of small-study effects (Egger’s test) was computed to explore the relationship between study-specificity effect size and study precision [Egger et al., 1997]. Additionally, trim and fill analysis [Duval and Tweedie, 2000] was performed to estimate the impact of missing studies due to publication bias in the final meta-analysis results. This approach ensured that the studies that caused the funnel plot’s asymmetry were trimmed, and then missing studies were filled in the funnel plot based on the bias-corrected overall estimate.

This study is part of a more extensive review to assess the global prevalence of dental caries among racially minoritized and privileged populations. The study selection process is outlined in the PRISMA 2020 flow diagram (Fig. 1). A total of 13,156 records were retrieved from searching nine electronic databases, ten publications were identified from citation searching and five records from searching websites. Of these, 5,617 were duplicates, 6,649 were ineligible after screening titles and abstracts, and the full text of 27 articles could not be retrieved: leaving 227 studies for full-text review. Another 75 studies were excluded after reading the full text (online suppl. Table S4). The final number of included studies was 178, reduced to 75 as the topic of interest in this publication was children aged 5–11 years [De Souza et al., 1967; Creighton, 1969; Kailis, 1971; Beal, 1973; Jensen et al., 1973; Castellanos, 1974; Menezes, 1974; Heifetz et al., 1976; Moreira and Vieira, 1977; Hunter, 1979; Kelly and Harvey, 1979; Schamschula et al., 1980; Manji, 1983; De Muñiz, 1985; Ran and Anaise, 1985; Perkins and Sweetman, 1986; Spencer et al., 1989; Laher, 1990; Bedi and Elton, 1991; Bedi et al., 1991, 2000; Grim et al., 1994; Korenstein et al., 1995; Aleksejuniene et al., 1996; Kaste et al., 1996; Davies et al., 1997; Prendergast et al., 1997; Vargas et al., 1998; Brown et al., 2000; Gray et al., 2000; Hallett and O’Rourke, 2002a, 2002b; Greer et al., 2003; Carvalho et al., 2004; Endean et al., 2004; Macek et al., 2004; Autio-Gold and Tomar, 2005; Chung et al., 2006; Jamieson et al., 2006b, 2006a, 2007b, 2010; Conway et al., 2007; Medina et al., 2008; Gowda et al., 2009; Phelan et al., 2009; Singh et al., 2011; Wigen and Wang, 2011; Caputo et al., 2012; Ardenghi et al., 2013; Kumar et al., 2013; Ferreira-Nóbilo et al., 2014; Ha, 2014; Ha et al., 2014; Ji et al., 2014; Masood et al., 2014; Sgan-Cohen et al., 2014; John et al., 2015; Lalloo et al., 2015; Matsuo et al., 2015; Arrow, 2016; Van Der Tas et al., 2016b; Mantonanaki et al., 2017; Miranda et al., 2018; Shi et al., 2018; Martin-Kerry et al., 2019; Qin et al., 2019; Fowler et al., 2020; Olatosi et al., 2020; Arantes et al., 2021; Aung et al., 2021; Bomfim et al., 2021; Darsie et al., 2021; Selvaraj et al., 2021].

Fig. 1.

Flow chart of search results (adapted from PRISMA, 2020 Flow Diagram).

Fig. 1.

Flow chart of search results (adapted from PRISMA, 2020 Flow Diagram).

Close modal

The main characteristics of the included studies are described in Table 1. Two studies were longitudinal [Masood et al., 2014; Van der Tas et al., 2016a], while all others were cross-sectional. The total number of children in the racially minoritized group was 186,850 and in the privileged population, 1,054,341. Samples in the included study were representative of the national population as the data were either from national surveys or long-term data from public schools. Eleven studies [Kelly and Harvey, 1979; Perkins and Sweetman, 1986; Vargas et al., 1998; Hallett and O’Rourke, 2002b, 2002a; Endean et al., 2004; Masood et al., 2014; Van der Tas et al., 2016a; Mantonanaki et al., 2017; Olatosi et al., 2020; Arantes et al., 2021] reported sample size estimation. Four studies were in Portuguese [De Souza et al., 1967; Castellanos, 1974; De Campos Mello et al., 2008; Ardenghi et al., 2013], two were in Chinese [Ji et al., 2014; Qin et al., 2019], with the remainder being in English. The year of publication ranged from 1967 to 2021. Most studies were from high-income countries (n = 54), 15 were from upper middle-income countries, four were from lower middle-income countries, and two were from low-income countries. The quality was assessed for all 75 studies (Table 1), and 23 studies were “very good,” 42 were “good,” and ten studies were “satisfactory; ” the full table can be found in figshare (https://doi.org/10.25909/23577993.v1). The main reasons for low scores were inconsistent systems (racial/ethnic) of classification of cases and control groups, data not being adjusted for other relevant risk and confounding factors, and poor statistical analysis, such as missing SD or CI for describing the findings.

Table 1.

Descriptive characteristics of the included studies (n = 75) and quality appraisal scores

Author, year, country, study designRegion, secondary datasetSampling technique, Sample size calculationCase (N)Controls (N)Age, yearsStudy quality scoreaConclusion
Aleksejuniene et al., 1996, Lithuansia, CS Schools from six regions throughout Lithuania Cluster sampling, NS Polish (107), Russian (189) Lithuanian (255) The DMFT scores for the Russians were lower whereas for Polish it was higher compared to Lithuanian 
Good 
Ardenghi et al., 2013, Brazil, CS Brazilian Oral Health Survey (2010) NS, representative sample Black (576), brown (3,220), yellow (140), Indigenous (52), based on skin colour Whites (3,229) The black, brown, yellow, and Indigenous people had more untreated caries than white people. 
Very good 
Arantes et al., 2021, Brazil, CS Indigenous dataset (2012–2014) Mato Grosso do Sul Brazilian state and non- Indigenous dataset (2010) national survey Stratified RS, Yes Indigenous (606) Non-Indigenous (1,124) The dmft/DMFT values were lower among Indigenous than non-Indigenous 
Good 
Arrow, 2016, Australia, CS Public dental service records NS, NS Aboriginals (268) Non-aboriginals (6,047) 5–10 The Aboriginal children had a higher dmft score 
Very good 
Aung et al., 2021, New Zealand, CS Titanium data set – clinical data – free dental examinations NS, NS Maori (4,526), Pacific (4,941), Asian (4,914) European (12,134) The ethnic group had a higher caries prevalence than Europeans. 
Good 
Autio-Gold and Tomar, 2005, USA, CS Schools – clinical fluoride varnish study NS, NS African Americans (148) Whites (52) 10 The whites had a lower caries score than African Americans 
Very good 
Beal, 1973, UK, CS Four areas – West Midland (1967–1970) NS, NS Negroes (333), Asian (248) Negro – West Indian Caucasoids (501) The Asians had the highest and the Negroes had the lowest mean number of decayed teeth than the Caucasoids. 
Asian - Indian and Pakistani British and Irish Good 
Bedi et al., 1991, UK, CS Glasgow, Trafford primary schools RS, NS Asian (Glasgow – 299; Trafford – 154) based on skin colour, facial appearance, and school records Whites (Glasgow – 246; Trafford – 69) based on skin colour, facial appearance, and school records 5 and 6 The Asian children had a higher dmft score than the white children 
Good 
Bedi et al., 1991, UK, CS Primary schools RS, NS Chinese (13), Asian (241), other ethnic groups (20) Whites (242) 10 No difference was observed in caries score for the ethnic and white groups 
Asian – Muslim, non-Muslim Good 
Bedi et al., 2000, UK, CS Schools and nurseries – old Trafford, Manchester, England, (1998 data only) NS, NS Afro-Caribbean (158), South Asian (English speaking mother – 187; non-English-speaking mother −313) Whites (213) White children had less caries score than other ethnic groups. 
Very good 
Bomfim et al., 2021, Brazil, CS SB Brazil 2010 Project PS cluster sampling, NS Pardo (3,064), black (559). White (3,073) The caries prevalence and severity were lower in whites than the blacks and Pardos. 
Based on skin colour; Pardo is between black and white Very good 
Brown et al., 2000, USA, CS NHANES I and III NS, NS Blacks (NS) Whites (NS) 2–10 Black children had higher caries experience than whites. 
Satisfactory 
Carvalho et al., 2004, Belgium, CS Primary schools (256), Brussels region (1998 cohort) NS, NS Non-Belgian (NS) Belgian (NS) The caries score was higher for non-Belgian than Belgian. 
Very good 
Castellanos, 1974, Brazil, CS Seven orphanages – city of Sao Paulo NS, NS Non-whites (463) Whites (397) 7–12 The was no significant difference in caries experience between non-white and white children. 
Very good 
Chung et al., 2006, USA, CS (Split according to year) Kindergarten Dental Screening Project (data, 2000–2001 and 2004–2005 recorded) NS, NS Asians (5,173), Hispanics (4,410), blacks (2062) Whites (1,536) 5–6 10 At all-time points, the prevalence of dental caries was lower in whites than other ethnic groups. 
Very good 
Conway et al., 2007, UK, CS SHBDEP survey, greater Glasgow (2001–2002) NS, NS Pakistanis (215) Whites (335) Pakistani children had a higher prevalence of dental caries than white children. 
Good 
Creighton, 1969, USA, CS (Split by age 6, 10) School RS, NS Negroes (502) Caucasians (366) NS 7 Good The Negroes had a poorer caries score than the Caucasians. 
Darsie et al., 2021, USA, CS Third grade California smile survey 2020 Stratified random sampling, Yes Asians (1196), black/African Americans (705), Latin (7,400) Whites (2083) The whites had a lower caries prevalence than other ethnic groups. 
Good 
Davies et al., 1997, Australia, CS CDS – Northern Territory, Australia RS, NS Aboriginals (836), Overseas (203), Non-Aboriginals (1,914) More decayed teeth in aboriginal and overseas children than Australian born. 
Born outside Australia Good 
De Campos Mello et al., 2008, Brazil, CS (Split by rural/urban status) Epidemiology Survey of Oral Health – São Paulo (1997–99) NS, NS Black or brown (11,606) Not black (13,111) 5–7 The black or brown children had a higher caries prevalence. 
Very good 
De Muñiz, 1985, Argentina, CS School – urban and rural areas NS, NS Amerindians (135) Caucasians (312) The mean decayed teeth were lower in Caucasians than in Amerindians. 
Good 
De Souza et al., 1967, Brazil, CS Schools NS, NS Non-whites (188) Whites (190) 8–12 The dental caries scores were lower among non-whites. 
Satisfactory 
Endean et al., 2004, Australia, CS Pitjantjatjaraand Yankunytjatjara-speaking communities at Nganampa Health (1999–2000) NS, Yes Anangu adults (317), Non-Indigenous (1,198) 5–6 The Anangu children had higher dental caries experience than the Australian population. 
Satisfactory 
Ferreira-Nóbilo et al., 2014, Brazil, CS Pre-school, school – Amparo, Brazil NS, NS Non-whites (33) Whites (170) The non-whites had a higher caries risk than whites. 
Very good 
Fowler et al., 2020, New Zealand, CS Orofacial cleft children, New Zealand NS, NS Maori (82), Pacific (35) Europeans (181) The Europeans had a lower dmft than the ethnic group. 
Very good 
Gowda et al., 2009, New Zealand, CS Schools – Kaitaia, Kaikohe, Kawakawa/Moerewa and Dargaville NS, NS Maori (236) Pakeha/other (133) white New Zealander 5–6 The dental caries prevalence and severity was high among Northlands. 
Good 
 
Gray et al., 2000, UK, CS Schools – Dudley Health district RS, NS South Asian (79) Whites (464) The prevalence of dental caries was higher among South Asians than white. 
Good 
Greer et al., 2003, USA, CS Public school children data set 1989 and 1999 RS, NS African American, Hispanics, Japanese, East-West mixed, Chinese, Koreans, Asian Mixed, Native Hawaiians, Samoan, Togan, Southwest Asians and Filipinos (NS) Caucasians (NS) 5–9 Asian and Pacific Islander children in contrast to Caucasian, African American, or Hispanic children had higher rates of dental caries. 
Good 
Grim et al., 1994, USA, CS Oklahoma population RS, NS Native Americans (457) Caucasians (456) 5–6 y The Native Americans had a higher dmft score than the Caucasians. 
Good 
Ha et al., 2014a, Australia, CS Child Dental Health Survey RS, NS Indigenous (4,032) Non-Indigenous (92,324) 5–6 The prevalence and severity were higher among Indigenous than non-Indigenous. 
Aboriginal,” “Torres Strait Islander,” “Aboriginal and Torres Strait IslanderorSouth Sea Islander” Very good 
Ha, 2014b, Australia, CS Child Dental Health Survey (2009) Systematic RS, NS Indigenous (NS) Non-Indigenous children (NS) 5–10 The dental caries score was higher among Indigenous children 
Good 
Hallett and O’Rourke, 2002a, Australia, CS State preschools – north Brisbane, Redcliffe, and Caboolture health districts. RS, Yes Asian (66), Aboriginals/Torres Strait Islander (48), South Sea Islander (182) Caucasians (2,073) 4–6 Compared to other ethnic groups the Caucasians had a lower dmft score. 
Good 
Hallett and O’Rourke, 2002b, Australia, CS North Brisbane region, preschool and grade 1 children RS, Yes Asians (127), Aboriginals (72), Others (90) Whites (2,835) 4–6 10 The caries prevalence and severity were lower for Caucasians. 
Very good 
Heifetz et al., 1976, USA, CS Nelson County Public School RS, NS Blacks (761) Whites (1,374) 6–8 Dental caries experience was similar for both groups. 
Satisfactory 
Hunter, 1979, New Zealand, CS Primary schools (Survey, 1977) Two-stage RS, NS Non-Europeans (241) Europeans (717) The non-Europeans had a higher caries score than Europeans. 
Good 
Jamieson et al., 2006a, Australia, CS Northern Territory School Dental Service in Child Dental Health Survey (2002–2003) RS, NS Indigenous (6,986) Non-Indigenous (12,758) 4–13 Indigenous children experienced higher mean dmft/DMFT levels than non-Indigenous counterparts. 
Satisfactory 
Jamieson et al., 2006b, Australia, CS Child Dental Health Survey from New South Wales, South Australia and the Northern Territory. RS, NS Indigenous (8,989) Non-Indigenous (259,998) 4–10 The Indigenous children had twice the caries score than the non-Indigenous children. 
Very good 
Jamieson et al., 2007a, Australia, CS School Dental Services South Australia dental services (2001–2006) NS, NS Regional Indigenous (756) Regional non-Indigenous (3,778) 5–10 The regional Indigenous children had a higher dmft/DMFT score. 
Satisfactory 
Jamieson et al., 2007b, Australia, CS Child Dental Health Survey New South Wales, South Australia and the Northern Territory. RS, NS Indigenous (NS) Non-Indigenous (NS) 4–14 The Indigenous children experienced higher caries prevalence and severity than non-Indigenous children. 
Good 
Jamieson et al., 2010, Australia, CS Aboriginal Birth Cohort and Child Dental Health Survey RS, NS Indigenous (145) Non-Indigenous (4,467) 6–8 Aboriginal experienced higher dental caries score than the general population 
Satisfactory 
Jensen et al., 1973, Uganda, CS Kampala primary schools NS, NS Asians (122) Africans (753) 6–15 The Asian children had higher dental caries than the Africans. 
Good 
Ji et al., 2014, China, CS Disabled persons - Butuo County, Muli Tibetan Autonomous County, and Huili County MSSC sampling, NS Yi (24) Han (52) 6–11 There was no significant difference in the caries rate and caries between Yi and Han people. 
Good 
John et al., 2015, India, CS Tribal children –Palamalai hills and Kolli hills. Urban children – Tiruchengode and Erode NS, NS Tribal (206) Urban children (411) 9–12 The tribal school children had a higher caries prevalence than the urban school children. 
Good 
Kailis, 1971, Australia, CS Aboriginal children – Carnarvon, Western Australia NS, NS Aborigines (84) Caucasians (248) 6–9 The Caucasian children had twice the caries prevalence than the Aboriginal children 
Satisfactory 
Kaste et al., 1996, USA, CS NHANES III, (1988–1991) NS, NS Blacks (489), non-Hispanic blacks (478), Mexican Americans (706) Non-Hispanic Whites (513) 5–9 The ethnic group had a higher caries prevalence than the non-Hispanic whites. 
Good 
Kelly and Harvey, 1979, USA, CS NHANES I (1971–74) NS, Yes Blacks (NS) Whites (NS) 6–11 The white children had a lower dental caries score. 
Good 
Korenstein et al., 1995, USA, CS Dental Branch, University of Texas. Convenience random, NS Hispanics (21), blacks (11) Whites (30) 6–7 Whites had a lower caries score than Hispanics and blacks 
Good 
Kumar et al., 2013, India, CS Schools – Chennai, tribal schools – Gudalur of Nilgiris district. MS stratified RS, NS Tribal children (743) Urban children (707) 6–14 The tribal children had a higher caries score than the urban children 
Good 
Laher, 1990, UK, CS Social Services Division 2 of Tower Hamlets. RS, NS Bangladeshi (203) Whites (73) 7, 9, 11 The Bangladeshi children had higher caries experience. 
Skin colour Good 
Lalloo et al., 2015, Australia, CS Child Dental Health Survey (2010) RS, NS Indigenous (6,817) Aboriginal, Torres Strait Islander, Aboriginal and Torres Strait Islander, South Sea Islander Non-Indigenous (91,255) 5–10 The caries score was higher among Indigenous than non-Indigenous children. 
Good 
Macek et al., 2004, USA, CS Oral Health Status of Maryland Schoolchildren, 200–2001. Probability-proportional-to-size, Yes Hispanics (152), non-Hispanic blacks (659), others (167) Non-Hispanic Whites (1,331) 5, 8 The racial-ethnic group had a higher caries score than the non-Hispanic whites 
Good 
Manji, 1983, Africa, CS Two primary schools located in Nairobi. RS, NS Asian (740) Africans (1,726) 4–12 Asian children had higher decayed and filled teeth and Africans had more missing teeth. 
Good 
Mantonanaki et al., 2017, Greece, CS Kindergarten school children RS CS, Yes Non-Greeks (78) Greeks (605) 4–6 The caries experience was higher for non-Greeks. 
Good 
Martin-Kerry et al., 2019, Australia, CS (split by location) Titanium – Victorian public oral health services (2012–13 and 2013–14) NS, NS Aboriginal (539) Non-Aboriginals (18,653) 5–6 The mean dmft scores were higher among Aboriginals than non-Aboriginals. 
Good 
Masood et al., 2014, Malaysia, LA (data from 2004–2009) School Dental Incremental Care Programme – Ministry of Health, Malaysia. (Data, 2004, 2007, 2009 only) MS CS RS, NS Chinese (570), Indians (449), Chinese (570) Malays (808) No difference was found among the ethnic groups. 
Good 
Matsuo et al., 2015, USA, CS North Carolina Oral Health Surveillance System, North Carolina Department of Public Instruction (2009–2010) NS, NS Blacks (18,253) Hispanics (11,202) Whites (40,635) Racial/ethnic disparities were present for dental caries. 
Very good 
Medina et al., 2008, Ecuador, CS Francisco de Orellana and Aguarico - Orellana province - north-eastern part of Ecuador PS, NS Indigenous (930) Naporunas Non-Indigenous (519) 6–12 The indigenous children had lower caries score than non-Indigenous children. 
Good 
Menezes, 1974, UK, CS Residents of Rangoon and Birmingham NS, NS Burmese (84) English (63) 10–12 Burmese children had lower caries severity 
Good 
Miranda et al., 2018, Brazil, CS Urban areas of Brazil, National Oral Health (SB Brazil, 2010) database NS, NS Indigenous (53) Non-Indigenous (7,286) Unequal differences in tooth decay between Indigenous and their national counterparts. 
Good 
Moreira and Vieira, 1977, Brazil, CS School – Piracicaba, State of Sao Paulo, Brazil NS, NS Blacks (612) Whites (671) 7–12 The blacks had lower DMFT score than the white children 
Good 
Olatosi et al., 2020, Nigeria, CS Local Government Areas of Lagos State MS sampling, Yes Hausa (4), Igbo (124), others (54) Yoruba (410) 5–16 10 The minoritized racial group had higher caries prevalence. 
Very good 
Perkins and Sweetman, 1986, UK, CS North-west London boroughs RS, Yes Afro-Caribbeans (33), Asians (81) Whites (145) The Asian group had a highest caries score among other groups. 
Good 
Phelan et al., 2009, Australia, CS Metropolitan and non-metropolitan public, Catholic and independent schools – New South Wales Representative sampling, NS Aboriginals (458) Non-aboriginals (6,591) 5–11 The indigenous children of NSW had poor DMFT score than the non-Aboriginal children. 
Satisfactory 
Prendergast et al., 1997, UK, CS Primary schools in Leeds. Stratified cluster, NS Afro-Caribbeans (54), Asians (107) Whites (304) The dmft scores were highest among Asians and lowest among Afro-Caribbeans 
Good 
Qin et al., 2019, China, CS Schools MS stratified and cluster RS,NS Minoritized (1,413) Majority (3,644) 10–12 The minoritized population had a higher caries prevalence. 
Tujia Han Very good 
Ran and Anaise, 1985, Jerusalem, CS 23 Schools RS, NS Arabs (229) Jewish (415) 6–8 Arab children had a higher caries score. 
Satisfactory 
Schamschula et al., 1980, Australia, CS Orana and Far West Health Region – New South Wales NS, NS Indigenous (128) Non-Indigenous (83) 6–11 The dental caries score was more severe in Aborigines than in Caucasians 
Good 
Selvaraj et al., 2021, USA, CS 18 Paediatric primary care practices in Northeast Ohio Parallel two-arm, cluster-randomized clinical trial, NS Blacks (451) Non-blacks (538) 3–6 Untreated primary decay and caries experience were 1.3 and 1.2 times higher among black children compared to non-black children. 
Very good 
Sgan-Cohen et al., 2014, Georgia, CS School – Tbilisi, Batumi and Kutaisi, Tlughi, Ambrolauri, Marneuli, and Akhaltsikhe. RS CS, NS Armenian (125), Azerbaijani (121) Georgian (710) 10 The caries experience was highest in Armenian and Azerbaijani than Georgian. 
Very good 
Shi et al., 2018, Canada, CS School – Public or Catholic – Calgary and Edmonton, Alberta Grade 1 & 2 schoolchildren MS PS, NS South-Asian (771), Filipino (345), Chinese (301), blacks (241), Arabs (193) Latin America (166) Indigenous (95), Mixed (544) Whites (2,944) 5–8 10 The Arabs and Indigenous children had the highest caries prevalence, and the whites had the lowest. 
Very good 
Singh et al., 2011, India, CS Six schools for Tribal children – Udupi district and government schools NS, NS Aborigine (418) Local (428) The dental caries occurrence was higher in Aborigine children than in the comparison group. 
Very good 
Spencer et al., 1989, Australia, CS State and independent schools – municipality of Brunswick, Melbourne (1977 & 1985) NS, NS Ethnic group (126) non-English speaker/reader English (121) speaker/readers 5–6 The dmft scores were higher among group that were non-English speaker/reader. 
Very good 
Van der Tas et al., 2016a, Netherland, LA Generation R study NS, Yes Surinamese-Hindustani (152), Surinamese-creole (154), Turkish (402), Dutch Antillean (161), Moroccan (308, Cape Verdean (172) Dutch (2,957) 5–6 10 The dental caries severity was higher among all the ethnic groups when compared against the Dutch. 
Very good 
Vargas et al., 1998, USA, CS NHANES III (1988–1994) MS PS, Yes African Americans (2,080), Mexican Americans (482) Non-Hispanic whites (6,208) 6–14 The caries prevalence and severity were higher among ethnic groups. 
Good 
Wigen and Wang, 2011, Norway, LS Norwegian Mother and Child Cohort Study – Norwegian Institute of Public Health and the Public Dental Services Akershus (The Dental Study) NS, NS Non-western (54) Asia, Africa, South America, Central America, and Eastern Europe Western origin (1,294) Children of non-Western parents had a higher caries score than parents of Western origin. 
Good 
Author, year, country, study designRegion, secondary datasetSampling technique, Sample size calculationCase (N)Controls (N)Age, yearsStudy quality scoreaConclusion
Aleksejuniene et al., 1996, Lithuansia, CS Schools from six regions throughout Lithuania Cluster sampling, NS Polish (107), Russian (189) Lithuanian (255) The DMFT scores for the Russians were lower whereas for Polish it was higher compared to Lithuanian 
Good 
Ardenghi et al., 2013, Brazil, CS Brazilian Oral Health Survey (2010) NS, representative sample Black (576), brown (3,220), yellow (140), Indigenous (52), based on skin colour Whites (3,229) The black, brown, yellow, and Indigenous people had more untreated caries than white people. 
Very good 
Arantes et al., 2021, Brazil, CS Indigenous dataset (2012–2014) Mato Grosso do Sul Brazilian state and non- Indigenous dataset (2010) national survey Stratified RS, Yes Indigenous (606) Non-Indigenous (1,124) The dmft/DMFT values were lower among Indigenous than non-Indigenous 
Good 
Arrow, 2016, Australia, CS Public dental service records NS, NS Aboriginals (268) Non-aboriginals (6,047) 5–10 The Aboriginal children had a higher dmft score 
Very good 
Aung et al., 2021, New Zealand, CS Titanium data set – clinical data – free dental examinations NS, NS Maori (4,526), Pacific (4,941), Asian (4,914) European (12,134) The ethnic group had a higher caries prevalence than Europeans. 
Good 
Autio-Gold and Tomar, 2005, USA, CS Schools – clinical fluoride varnish study NS, NS African Americans (148) Whites (52) 10 The whites had a lower caries score than African Americans 
Very good 
Beal, 1973, UK, CS Four areas – West Midland (1967–1970) NS, NS Negroes (333), Asian (248) Negro – West Indian Caucasoids (501) The Asians had the highest and the Negroes had the lowest mean number of decayed teeth than the Caucasoids. 
Asian - Indian and Pakistani British and Irish Good 
Bedi et al., 1991, UK, CS Glasgow, Trafford primary schools RS, NS Asian (Glasgow – 299; Trafford – 154) based on skin colour, facial appearance, and school records Whites (Glasgow – 246; Trafford – 69) based on skin colour, facial appearance, and school records 5 and 6 The Asian children had a higher dmft score than the white children 
Good 
Bedi et al., 1991, UK, CS Primary schools RS, NS Chinese (13), Asian (241), other ethnic groups (20) Whites (242) 10 No difference was observed in caries score for the ethnic and white groups 
Asian – Muslim, non-Muslim Good 
Bedi et al., 2000, UK, CS Schools and nurseries – old Trafford, Manchester, England, (1998 data only) NS, NS Afro-Caribbean (158), South Asian (English speaking mother – 187; non-English-speaking mother −313) Whites (213) White children had less caries score than other ethnic groups. 
Very good 
Bomfim et al., 2021, Brazil, CS SB Brazil 2010 Project PS cluster sampling, NS Pardo (3,064), black (559). White (3,073) The caries prevalence and severity were lower in whites than the blacks and Pardos. 
Based on skin colour; Pardo is between black and white Very good 
Brown et al., 2000, USA, CS NHANES I and III NS, NS Blacks (NS) Whites (NS) 2–10 Black children had higher caries experience than whites. 
Satisfactory 
Carvalho et al., 2004, Belgium, CS Primary schools (256), Brussels region (1998 cohort) NS, NS Non-Belgian (NS) Belgian (NS) The caries score was higher for non-Belgian than Belgian. 
Very good 
Castellanos, 1974, Brazil, CS Seven orphanages – city of Sao Paulo NS, NS Non-whites (463) Whites (397) 7–12 The was no significant difference in caries experience between non-white and white children. 
Very good 
Chung et al., 2006, USA, CS (Split according to year) Kindergarten Dental Screening Project (data, 2000–2001 and 2004–2005 recorded) NS, NS Asians (5,173), Hispanics (4,410), blacks (2062) Whites (1,536) 5–6 10 At all-time points, the prevalence of dental caries was lower in whites than other ethnic groups. 
Very good 
Conway et al., 2007, UK, CS SHBDEP survey, greater Glasgow (2001–2002) NS, NS Pakistanis (215) Whites (335) Pakistani children had a higher prevalence of dental caries than white children. 
Good 
Creighton, 1969, USA, CS (Split by age 6, 10) School RS, NS Negroes (502) Caucasians (366) NS 7 Good The Negroes had a poorer caries score than the Caucasians. 
Darsie et al., 2021, USA, CS Third grade California smile survey 2020 Stratified random sampling, Yes Asians (1196), black/African Americans (705), Latin (7,400) Whites (2083) The whites had a lower caries prevalence than other ethnic groups. 
Good 
Davies et al., 1997, Australia, CS CDS – Northern Territory, Australia RS, NS Aboriginals (836), Overseas (203), Non-Aboriginals (1,914) More decayed teeth in aboriginal and overseas children than Australian born. 
Born outside Australia Good 
De Campos Mello et al., 2008, Brazil, CS (Split by rural/urban status) Epidemiology Survey of Oral Health – São Paulo (1997–99) NS, NS Black or brown (11,606) Not black (13,111) 5–7 The black or brown children had a higher caries prevalence. 
Very good 
De Muñiz, 1985, Argentina, CS School – urban and rural areas NS, NS Amerindians (135) Caucasians (312) The mean decayed teeth were lower in Caucasians than in Amerindians. 
Good 
De Souza et al., 1967, Brazil, CS Schools NS, NS Non-whites (188) Whites (190) 8–12 The dental caries scores were lower among non-whites. 
Satisfactory 
Endean et al., 2004, Australia, CS Pitjantjatjaraand Yankunytjatjara-speaking communities at Nganampa Health (1999–2000) NS, Yes Anangu adults (317), Non-Indigenous (1,198) 5–6 The Anangu children had higher dental caries experience than the Australian population. 
Satisfactory 
Ferreira-Nóbilo et al., 2014, Brazil, CS Pre-school, school – Amparo, Brazil NS, NS Non-whites (33) Whites (170) The non-whites had a higher caries risk than whites. 
Very good 
Fowler et al., 2020, New Zealand, CS Orofacial cleft children, New Zealand NS, NS Maori (82), Pacific (35) Europeans (181) The Europeans had a lower dmft than the ethnic group. 
Very good 
Gowda et al., 2009, New Zealand, CS Schools – Kaitaia, Kaikohe, Kawakawa/Moerewa and Dargaville NS, NS Maori (236) Pakeha/other (133) white New Zealander 5–6 The dental caries prevalence and severity was high among Northlands. 
Good 
 
Gray et al., 2000, UK, CS Schools – Dudley Health district RS, NS South Asian (79) Whites (464) The prevalence of dental caries was higher among South Asians than white. 
Good 
Greer et al., 2003, USA, CS Public school children data set 1989 and 1999 RS, NS African American, Hispanics, Japanese, East-West mixed, Chinese, Koreans, Asian Mixed, Native Hawaiians, Samoan, Togan, Southwest Asians and Filipinos (NS) Caucasians (NS) 5–9 Asian and Pacific Islander children in contrast to Caucasian, African American, or Hispanic children had higher rates of dental caries. 
Good 
Grim et al., 1994, USA, CS Oklahoma population RS, NS Native Americans (457) Caucasians (456) 5–6 y The Native Americans had a higher dmft score than the Caucasians. 
Good 
Ha et al., 2014a, Australia, CS Child Dental Health Survey RS, NS Indigenous (4,032) Non-Indigenous (92,324) 5–6 The prevalence and severity were higher among Indigenous than non-Indigenous. 
Aboriginal,” “Torres Strait Islander,” “Aboriginal and Torres Strait IslanderorSouth Sea Islander” Very good 
Ha, 2014b, Australia, CS Child Dental Health Survey (2009) Systematic RS, NS Indigenous (NS) Non-Indigenous children (NS) 5–10 The dental caries score was higher among Indigenous children 
Good 
Hallett and O’Rourke, 2002a, Australia, CS State preschools – north Brisbane, Redcliffe, and Caboolture health districts. RS, Yes Asian (66), Aboriginals/Torres Strait Islander (48), South Sea Islander (182) Caucasians (2,073) 4–6 Compared to other ethnic groups the Caucasians had a lower dmft score. 
Good 
Hallett and O’Rourke, 2002b, Australia, CS North Brisbane region, preschool and grade 1 children RS, Yes Asians (127), Aboriginals (72), Others (90) Whites (2,835) 4–6 10 The caries prevalence and severity were lower for Caucasians. 
Very good 
Heifetz et al., 1976, USA, CS Nelson County Public School RS, NS Blacks (761) Whites (1,374) 6–8 Dental caries experience was similar for both groups. 
Satisfactory 
Hunter, 1979, New Zealand, CS Primary schools (Survey, 1977) Two-stage RS, NS Non-Europeans (241) Europeans (717) The non-Europeans had a higher caries score than Europeans. 
Good 
Jamieson et al., 2006a, Australia, CS Northern Territory School Dental Service in Child Dental Health Survey (2002–2003) RS, NS Indigenous (6,986) Non-Indigenous (12,758) 4–13 Indigenous children experienced higher mean dmft/DMFT levels than non-Indigenous counterparts. 
Satisfactory 
Jamieson et al., 2006b, Australia, CS Child Dental Health Survey from New South Wales, South Australia and the Northern Territory. RS, NS Indigenous (8,989) Non-Indigenous (259,998) 4–10 The Indigenous children had twice the caries score than the non-Indigenous children. 
Very good 
Jamieson et al., 2007a, Australia, CS School Dental Services South Australia dental services (2001–2006) NS, NS Regional Indigenous (756) Regional non-Indigenous (3,778) 5–10 The regional Indigenous children had a higher dmft/DMFT score. 
Satisfactory 
Jamieson et al., 2007b, Australia, CS Child Dental Health Survey New South Wales, South Australia and the Northern Territory. RS, NS Indigenous (NS) Non-Indigenous (NS) 4–14 The Indigenous children experienced higher caries prevalence and severity than non-Indigenous children. 
Good 
Jamieson et al., 2010, Australia, CS Aboriginal Birth Cohort and Child Dental Health Survey RS, NS Indigenous (145) Non-Indigenous (4,467) 6–8 Aboriginal experienced higher dental caries score than the general population 
Satisfactory 
Jensen et al., 1973, Uganda, CS Kampala primary schools NS, NS Asians (122) Africans (753) 6–15 The Asian children had higher dental caries than the Africans. 
Good 
Ji et al., 2014, China, CS Disabled persons - Butuo County, Muli Tibetan Autonomous County, and Huili County MSSC sampling, NS Yi (24) Han (52) 6–11 There was no significant difference in the caries rate and caries between Yi and Han people. 
Good 
John et al., 2015, India, CS Tribal children –Palamalai hills and Kolli hills. Urban children – Tiruchengode and Erode NS, NS Tribal (206) Urban children (411) 9–12 The tribal school children had a higher caries prevalence than the urban school children. 
Good 
Kailis, 1971, Australia, CS Aboriginal children – Carnarvon, Western Australia NS, NS Aborigines (84) Caucasians (248) 6–9 The Caucasian children had twice the caries prevalence than the Aboriginal children 
Satisfactory 
Kaste et al., 1996, USA, CS NHANES III, (1988–1991) NS, NS Blacks (489), non-Hispanic blacks (478), Mexican Americans (706) Non-Hispanic Whites (513) 5–9 The ethnic group had a higher caries prevalence than the non-Hispanic whites. 
Good 
Kelly and Harvey, 1979, USA, CS NHANES I (1971–74) NS, Yes Blacks (NS) Whites (NS) 6–11 The white children had a lower dental caries score. 
Good 
Korenstein et al., 1995, USA, CS Dental Branch, University of Texas. Convenience random, NS Hispanics (21), blacks (11) Whites (30) 6–7 Whites had a lower caries score than Hispanics and blacks 
Good 
Kumar et al., 2013, India, CS Schools – Chennai, tribal schools – Gudalur of Nilgiris district. MS stratified RS, NS Tribal children (743) Urban children (707) 6–14 The tribal children had a higher caries score than the urban children 
Good 
Laher, 1990, UK, CS Social Services Division 2 of Tower Hamlets. RS, NS Bangladeshi (203) Whites (73) 7, 9, 11 The Bangladeshi children had higher caries experience. 
Skin colour Good 
Lalloo et al., 2015, Australia, CS Child Dental Health Survey (2010) RS, NS Indigenous (6,817) Aboriginal, Torres Strait Islander, Aboriginal and Torres Strait Islander, South Sea Islander Non-Indigenous (91,255) 5–10 The caries score was higher among Indigenous than non-Indigenous children. 
Good 
Macek et al., 2004, USA, CS Oral Health Status of Maryland Schoolchildren, 200–2001. Probability-proportional-to-size, Yes Hispanics (152), non-Hispanic blacks (659), others (167) Non-Hispanic Whites (1,331) 5, 8 The racial-ethnic group had a higher caries score than the non-Hispanic whites 
Good 
Manji, 1983, Africa, CS Two primary schools located in Nairobi. RS, NS Asian (740) Africans (1,726) 4–12 Asian children had higher decayed and filled teeth and Africans had more missing teeth. 
Good 
Mantonanaki et al., 2017, Greece, CS Kindergarten school children RS CS, Yes Non-Greeks (78) Greeks (605) 4–6 The caries experience was higher for non-Greeks. 
Good 
Martin-Kerry et al., 2019, Australia, CS (split by location) Titanium – Victorian public oral health services (2012–13 and 2013–14) NS, NS Aboriginal (539) Non-Aboriginals (18,653) 5–6 The mean dmft scores were higher among Aboriginals than non-Aboriginals. 
Good 
Masood et al., 2014, Malaysia, LA (data from 2004–2009) School Dental Incremental Care Programme – Ministry of Health, Malaysia. (Data, 2004, 2007, 2009 only) MS CS RS, NS Chinese (570), Indians (449), Chinese (570) Malays (808) No difference was found among the ethnic groups. 
Good 
Matsuo et al., 2015, USA, CS North Carolina Oral Health Surveillance System, North Carolina Department of Public Instruction (2009–2010) NS, NS Blacks (18,253) Hispanics (11,202) Whites (40,635) Racial/ethnic disparities were present for dental caries. 
Very good 
Medina et al., 2008, Ecuador, CS Francisco de Orellana and Aguarico - Orellana province - north-eastern part of Ecuador PS, NS Indigenous (930) Naporunas Non-Indigenous (519) 6–12 The indigenous children had lower caries score than non-Indigenous children. 
Good 
Menezes, 1974, UK, CS Residents of Rangoon and Birmingham NS, NS Burmese (84) English (63) 10–12 Burmese children had lower caries severity 
Good 
Miranda et al., 2018, Brazil, CS Urban areas of Brazil, National Oral Health (SB Brazil, 2010) database NS, NS Indigenous (53) Non-Indigenous (7,286) Unequal differences in tooth decay between Indigenous and their national counterparts. 
Good 
Moreira and Vieira, 1977, Brazil, CS School – Piracicaba, State of Sao Paulo, Brazil NS, NS Blacks (612) Whites (671) 7–12 The blacks had lower DMFT score than the white children 
Good 
Olatosi et al., 2020, Nigeria, CS Local Government Areas of Lagos State MS sampling, Yes Hausa (4), Igbo (124), others (54) Yoruba (410) 5–16 10 The minoritized racial group had higher caries prevalence. 
Very good 
Perkins and Sweetman, 1986, UK, CS North-west London boroughs RS, Yes Afro-Caribbeans (33), Asians (81) Whites (145) The Asian group had a highest caries score among other groups. 
Good 
Phelan et al., 2009, Australia, CS Metropolitan and non-metropolitan public, Catholic and independent schools – New South Wales Representative sampling, NS Aboriginals (458) Non-aboriginals (6,591) 5–11 The indigenous children of NSW had poor DMFT score than the non-Aboriginal children. 
Satisfactory 
Prendergast et al., 1997, UK, CS Primary schools in Leeds. Stratified cluster, NS Afro-Caribbeans (54), Asians (107) Whites (304) The dmft scores were highest among Asians and lowest among Afro-Caribbeans 
Good 
Qin et al., 2019, China, CS Schools MS stratified and cluster RS,NS Minoritized (1,413) Majority (3,644) 10–12 The minoritized population had a higher caries prevalence. 
Tujia Han Very good 
Ran and Anaise, 1985, Jerusalem, CS 23 Schools RS, NS Arabs (229) Jewish (415) 6–8 Arab children had a higher caries score. 
Satisfactory 
Schamschula et al., 1980, Australia, CS Orana and Far West Health Region – New South Wales NS, NS Indigenous (128) Non-Indigenous (83) 6–11 The dental caries score was more severe in Aborigines than in Caucasians 
Good 
Selvaraj et al., 2021, USA, CS 18 Paediatric primary care practices in Northeast Ohio Parallel two-arm, cluster-randomized clinical trial, NS Blacks (451) Non-blacks (538) 3–6 Untreated primary decay and caries experience were 1.3 and 1.2 times higher among black children compared to non-black children. 
Very good 
Sgan-Cohen et al., 2014, Georgia, CS School – Tbilisi, Batumi and Kutaisi, Tlughi, Ambrolauri, Marneuli, and Akhaltsikhe. RS CS, NS Armenian (125), Azerbaijani (121) Georgian (710) 10 The caries experience was highest in Armenian and Azerbaijani than Georgian. 
Very good 
Shi et al., 2018, Canada, CS School – Public or Catholic – Calgary and Edmonton, Alberta Grade 1 & 2 schoolchildren MS PS, NS South-Asian (771), Filipino (345), Chinese (301), blacks (241), Arabs (193) Latin America (166) Indigenous (95), Mixed (544) Whites (2,944) 5–8 10 The Arabs and Indigenous children had the highest caries prevalence, and the whites had the lowest. 
Very good 
Singh et al., 2011, India, CS Six schools for Tribal children – Udupi district and government schools NS, NS Aborigine (418) Local (428) The dental caries occurrence was higher in Aborigine children than in the comparison group. 
Very good 
Spencer et al., 1989, Australia, CS State and independent schools – municipality of Brunswick, Melbourne (1977 & 1985) NS, NS Ethnic group (126) non-English speaker/reader English (121) speaker/readers 5–6 The dmft scores were higher among group that were non-English speaker/reader. 
Very good 
Van der Tas et al., 2016a, Netherland, LA Generation R study NS, Yes Surinamese-Hindustani (152), Surinamese-creole (154), Turkish (402), Dutch Antillean (161), Moroccan (308, Cape Verdean (172) Dutch (2,957) 5–6 10 The dental caries severity was higher among all the ethnic groups when compared against the Dutch. 
Very good 
Vargas et al., 1998, USA, CS NHANES III (1988–1994) MS PS, Yes African Americans (2,080), Mexican Americans (482) Non-Hispanic whites (6,208) 6–14 The caries prevalence and severity were higher among ethnic groups. 
Good 
Wigen and Wang, 2011, Norway, LS Norwegian Mother and Child Cohort Study – Norwegian Institute of Public Health and the Public Dental Services Akershus (The Dental Study) NS, NS Non-western (54) Asia, Africa, South America, Central America, and Eastern Europe Western origin (1,294) Children of non-Western parents had a higher caries score than parents of Western origin. 
Good 

ARCPOH, Australian Research Centre for Population Oral Health; COHNAC, California Oral Health Needs Assessment of Children; CDS, Community Dental Service; CS, Cross-Sectional Study Design; LA, Longitudinal Analysis; MS, Multi-Stage; NCOHS, National Children’s Oral Health Survey; NDA, National Dental Association; NHANES, National Health and Nutrition Examination Survey; NS, Not Specified; NSAOH, National Survey of Adult Oral Health; PCF, Party Community Foundation; PS, Probability sampling; RS, Random sampling; SA, South Australia; SC, Stratified Clustered; SFDS, San Francisco Dental Society; SHBDEP, Scottish Health Board Dental Epidemiology Program; UK, United Kingdom; USA, United States of America.

aThe Newcastle-Ottawa Scale quality score: Very good studies: 9–10 points, Good studies: 7–8 points, Satisfactory studies: 5–6 points, Unsatisfactory studies: 0–4 points.

Most authors relied on self-reporting for assessing race. The most common (n = 22) taxonomic classification used was the cultural system, based on similar language, religion, traditions, and history. The second most common (n = 20) was the prioritization system, where the population is dichotomized (e.g., minority vs. majority, Indigenous vs. non-Indigenous). Few authors used the country of origin to identify race. In contrast, 15 authors used physical appearance, such as “skin colour” and facial appearance. The Office of Management and Budget classification was used by studies originating in the USA (Table 2).

Table 2.

Methods, concepts, classification used for race/ethnicity from included studies

Author, year, countryMethods used for assessingaConcepts usedbTaxonomic classificationcExplanation of effectsd
Aleksejuniene et al., 1996, Lithuania Self-reported Ethnicity Country of origin Yes 
Ardenghi et al., 2013, Brazil Self-reported Not stated Physical appearance No 
Arantes et al., 2021, Brazil Self-reported Ethnicity Prioritization Yes 
Arrow, 2016, Australia Self-reported Not stated Prioritization No 
Aung et al., 2021, New Zealand Self-reported Ethnicity Country of origin No 
Autio-Gold and Tomar, 2005, USA Self-reported Race Cultural No 
Beal, 1973, UK Defined by others Ethnicity Physical appearance No 
Bedi et al., 1991, UK Preexisting record Ethnicity Physical appearance Yes 
Bedi et al., 1991, UK Preexisting record Ethnicity Cultural Yes 
Bedi et al., 2000, UK Self-reported Ethnicity Cultural No 
Bomfim et al., 2021, Brazil Self-reported Ethnicity Physical appearance No 
Brown et al., 2000, USA, CS Defined by others Race Physical appearance No 
Carvalho et al., 2004, Belgium Self-reported Ethnicity Physical appearance No 
Castellanos, 1974, Brazil Defined by others Not stated Physical appearance No 
Chung et al., 2006, USA Self-reported Both Cultural No 
Conway et al., 2007, UK Self-reported Ethnicity Country of origin No 
Castellanos, 1974, USA Self-reported Race Physical appearance No 
Darsie et al., 2021, USA Self-reported Both Country of origin No 
Davies et al., 1997, UK Self-reported Race Cultural No 
De Campos Mello et al., 2008, Brazil Defined by others Not stated Physical appearance No 
De Muñiz, 1985, Argentina Self-reported Ethnicity Cultural No 
De Souza et al., 1967, Brazil Defined by others Not stated Physical appearance No 
Endean et al., 2004, Australia Self-reported Race Prioritization No 
Ferreira-Nóbilo et al., 2014, Brazil Self-reported Ethnicity Physical appearance No 
Fowler et al., 2020, New Zealand Self-reported Ethnicity Cultural No 
Gowda et al., 2009, New Zealand Self-reported Ethnicity Prioritization No 
Gray et al., 2000, UK Self-reported Ethnicity Country of origin No 
Greer et al., 2003, USA Self-reported Ethnicity Country of origin No 
Grim et al., 1994, USA Self-reported Ethnicity Country of origin No 
Ha et al., 2014a, Australia Self-reported Not stated Prioritization No 
Ha et al., 2014b, Australia Self-reported Not stated Prioritization No 
Hallett and O’Rourke, 2002a, Australia Preexisting record Ethnicity Cultural No 
Hallett and O’Rourke, 2002b, Australia Preexisting record Ethnicity Cultural No 
Heifetz et al., 1976, USA Self-reported Ethnicity Physical appearance No 
Hunter, 1979, New Zealand Self-reported Race Prioritization No 
Jamieson et al., 2006a, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2006b, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2007a, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2007b, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2010, Australia Self-reported Not stated Prioritization Yes 
Jensen et al., 1973, Uganda Self-reported Race Country of origin Yes 
Ji et al., 2014, China Not stated Not stated Cultural No 
John et al., 2015, India Self-reported Not stated Cultural No 
Kailis, 1971, Australia Self-reported Race Prioritization No 
Kaste et al., 1996, USA Self-reported Both OMB classification No 
Kelly and Harvey, 1979, USA Self-reported Race Physical appearance Yes 
Korenstein et al., 1995, USA Self-reported Both Cultural No 
Kumar et al., 2013, India Self-reported Not stated Cultural Yes 
Laher, 1990, UK Self-reported Both Physical appearance No 
Lalloo et al., 2015, Australia Preexisting record Not stated Prioritization Yes 
Macek et al., 2004, USA Defined by others Both OMB classification No 
Manji, 1983, Africa Preexisting record Race Country of origin No 
Mantonanaki et al., 2017, Greece Preexisting record Ethnicity Prioritization No 
Martin-Kerry et al., 2019, Australia Defined by others Not stated Prioritization Yes 
Masood et al., 2014, Malaysia Self-reported Ethnicity Country of origin Yes 
Matsuo et al., 2015, USA Self-reported Ethnicity Country of origin No 
Medina et al., 2008, Ecuador Self-reported Ethnicity Prioritization Yes 
Menezes, 1974, UK Self-reported Ethnicity Country of origin Yes 
Miranda et al., 2018, Brazil Self-reported Both Prioritization Yes 
Moreira and Vieira, 1977, Brazil Not stated Race Physical appearance No 
Olatosi et al., 2020, Nigeria Self-reported Ethnicity Cultural No 
Perkins and Sweetman, 1986, UK Self-reported Ethnicity Country of origin No 
Phelan et al., 2009, Australia Self-reported Race Prioritization No 
Prendergast et al., 1997, UK Pre-existing record Ethnicity Country of origin No 
Qin et al., 2019, China Self-reported Ethnicity Cultural No 
Ran and Anaise, 1985, Jerusalem Not stated Not stated Cultural No 
Schamschula et al., 1980, Australia Self-reported Not stated Prioritization Yes 
Selvaraj et al., 2021, USA Self-reported Both OMB classification Yes 
Sgan-Cohen et al., 2014, Georgia Self-reported Ethnicity Cultural No 
Shi et al., 2018, Canada Self-reported Ethnicity Cultural Yes 
Singh et al., 2011, India Self-reported Not stated Cultural No 
Spencer et al., 1989, Australia Self-reported Ethnicity Cultural No 
Van der Tas et al., 2016a, Netherland Pre-existing record Ethnicity Cultural No 
Vargas et al., 1998, USA Self-reported Ethnicity OMB classification No 
Wigen and Wang, 2011, Norway Self-reported Not stated Cultural No 
Author, year, countryMethods used for assessingaConcepts usedbTaxonomic classificationcExplanation of effectsd
Aleksejuniene et al., 1996, Lithuania Self-reported Ethnicity Country of origin Yes 
Ardenghi et al., 2013, Brazil Self-reported Not stated Physical appearance No 
Arantes et al., 2021, Brazil Self-reported Ethnicity Prioritization Yes 
Arrow, 2016, Australia Self-reported Not stated Prioritization No 
Aung et al., 2021, New Zealand Self-reported Ethnicity Country of origin No 
Autio-Gold and Tomar, 2005, USA Self-reported Race Cultural No 
Beal, 1973, UK Defined by others Ethnicity Physical appearance No 
Bedi et al., 1991, UK Preexisting record Ethnicity Physical appearance Yes 
Bedi et al., 1991, UK Preexisting record Ethnicity Cultural Yes 
Bedi et al., 2000, UK Self-reported Ethnicity Cultural No 
Bomfim et al., 2021, Brazil Self-reported Ethnicity Physical appearance No 
Brown et al., 2000, USA, CS Defined by others Race Physical appearance No 
Carvalho et al., 2004, Belgium Self-reported Ethnicity Physical appearance No 
Castellanos, 1974, Brazil Defined by others Not stated Physical appearance No 
Chung et al., 2006, USA Self-reported Both Cultural No 
Conway et al., 2007, UK Self-reported Ethnicity Country of origin No 
Castellanos, 1974, USA Self-reported Race Physical appearance No 
Darsie et al., 2021, USA Self-reported Both Country of origin No 
Davies et al., 1997, UK Self-reported Race Cultural No 
De Campos Mello et al., 2008, Brazil Defined by others Not stated Physical appearance No 
De Muñiz, 1985, Argentina Self-reported Ethnicity Cultural No 
De Souza et al., 1967, Brazil Defined by others Not stated Physical appearance No 
Endean et al., 2004, Australia Self-reported Race Prioritization No 
Ferreira-Nóbilo et al., 2014, Brazil Self-reported Ethnicity Physical appearance No 
Fowler et al., 2020, New Zealand Self-reported Ethnicity Cultural No 
Gowda et al., 2009, New Zealand Self-reported Ethnicity Prioritization No 
Gray et al., 2000, UK Self-reported Ethnicity Country of origin No 
Greer et al., 2003, USA Self-reported Ethnicity Country of origin No 
Grim et al., 1994, USA Self-reported Ethnicity Country of origin No 
Ha et al., 2014a, Australia Self-reported Not stated Prioritization No 
Ha et al., 2014b, Australia Self-reported Not stated Prioritization No 
Hallett and O’Rourke, 2002a, Australia Preexisting record Ethnicity Cultural No 
Hallett and O’Rourke, 2002b, Australia Preexisting record Ethnicity Cultural No 
Heifetz et al., 1976, USA Self-reported Ethnicity Physical appearance No 
Hunter, 1979, New Zealand Self-reported Race Prioritization No 
Jamieson et al., 2006a, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2006b, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2007a, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2007b, Australia Self-reported Not stated Prioritization Yes 
Jamieson et al., 2010, Australia Self-reported Not stated Prioritization Yes 
Jensen et al., 1973, Uganda Self-reported Race Country of origin Yes 
Ji et al., 2014, China Not stated Not stated Cultural No 
John et al., 2015, India Self-reported Not stated Cultural No 
Kailis, 1971, Australia Self-reported Race Prioritization No 
Kaste et al., 1996, USA Self-reported Both OMB classification No 
Kelly and Harvey, 1979, USA Self-reported Race Physical appearance Yes 
Korenstein et al., 1995, USA Self-reported Both Cultural No 
Kumar et al., 2013, India Self-reported Not stated Cultural Yes 
Laher, 1990, UK Self-reported Both Physical appearance No 
Lalloo et al., 2015, Australia Preexisting record Not stated Prioritization Yes 
Macek et al., 2004, USA Defined by others Both OMB classification No 
Manji, 1983, Africa Preexisting record Race Country of origin No 
Mantonanaki et al., 2017, Greece Preexisting record Ethnicity Prioritization No 
Martin-Kerry et al., 2019, Australia Defined by others Not stated Prioritization Yes 
Masood et al., 2014, Malaysia Self-reported Ethnicity Country of origin Yes 
Matsuo et al., 2015, USA Self-reported Ethnicity Country of origin No 
Medina et al., 2008, Ecuador Self-reported Ethnicity Prioritization Yes 
Menezes, 1974, UK Self-reported Ethnicity Country of origin Yes 
Miranda et al., 2018, Brazil Self-reported Both Prioritization Yes 
Moreira and Vieira, 1977, Brazil Not stated Race Physical appearance No 
Olatosi et al., 2020, Nigeria Self-reported Ethnicity Cultural No 
Perkins and Sweetman, 1986, UK Self-reported Ethnicity Country of origin No 
Phelan et al., 2009, Australia Self-reported Race Prioritization No 
Prendergast et al., 1997, UK Pre-existing record Ethnicity Country of origin No 
Qin et al., 2019, China Self-reported Ethnicity Cultural No 
Ran and Anaise, 1985, Jerusalem Not stated Not stated Cultural No 
Schamschula et al., 1980, Australia Self-reported Not stated Prioritization Yes 
Selvaraj et al., 2021, USA Self-reported Both OMB classification Yes 
Sgan-Cohen et al., 2014, Georgia Self-reported Ethnicity Cultural No 
Shi et al., 2018, Canada Self-reported Ethnicity Cultural Yes 
Singh et al., 2011, India Self-reported Not stated Cultural No 
Spencer et al., 1989, Australia Self-reported Ethnicity Cultural No 
Van der Tas et al., 2016a, Netherland Pre-existing record Ethnicity Cultural No 
Vargas et al., 1998, USA Self-reported Ethnicity OMB classification No 
Wigen and Wang, 2011, Norway Self-reported Not stated Cultural No 

USA, United States of America; UK, United Kingdom; OMB, Office of Management and Budget.

aMethods of assessing race and ethnicity included: Self-reported, pre-existing records, defined by others, not specified.

bConcepts used: Race, ethnicity, both, not stated.

cTaxonomic classification: 1, Country of origin. 2, Cultural based on religion, traditions, history, and language. 3, Physical appearances such as the colour of skin, and facial appearance. 4, OMB, Office of Management and Budget, which classifies an individual as ethnic categories such as Hispanic or Latino or Race categories such as white, black or African American, American Indian or Alaska Native, Asian, and Native Hawaiian, or Other Pacific Islander. 5 Prioritization based on dividing the population into two groups such as Indigenous and non-Indigenous, Maori and non-Maori.

dExplanation of using race and ethnicity as an exposure variable.

The mean difference in dmft score was 2.30 (0.45, 4.15) higher among minority children than the privileged children’s population (Fig. 2). The subgroup meta-analysis for high-income countries with 42 studies showed a score SMD 2.64 higher (0.52, 4.76) for minority than the privileged population. Racially minoritized children from Australia had the highest dmft score of SMD 6.22 (1.38, 11.05), followed by New Zealand (0.59; 0.44, 0.74), Britain (0.17; −0.01, 0.35), and the USA (0.18; 0.03, 0.32) (online suppl. Fig. S1). Cumulative analysis also confirmed that the mean dmft score doubled over the last 2 decades (1973–2021) (online suppl. Fig. S2). The potential outliers were Hallett and O’Rourke [2002b] (subdivided into three subgroups based on race categories) and Martin-Kerry et al. [2019] (subdivided into three subgroups based on city, inner, and outer regional), as shown in leave-one-out analysis (online suppl. Fig. S3A), with the Galbraith plot showing these two apparent outliers in the top right corner (online suppl. Fig. S3B). In the CE funnel plot, most studies were of high precision with a large sample size and no gross asymmetry observed (online suppl. Fig. S4A). The regression based on Eggers’s test showed there could have been a small study effect (online suppl. Fig. S4B). The results remained unchanged after applying the trim and fill method, as there was no gross asymmetry in the CE funnel plot.

Fig. 2.

Forest plot of prevalence of dmft >0 among children.

Fig. 2.

Forest plot of prevalence of dmft >0 among children.

Close modal

The mean prevalence of decayed teeth >0 was 23% (95% CI: 16, 31) (Fig. 3) higher among racially minoritized children. The heterogeneity score was 96.93%. High-income countries showed high prevalence estimates of 26% (95% CI: 0.17, 0.35), and, when countries were analysed separately, all showed high prevalence estimates, such as USA (n = 10, 19%; 0.12, 0.26) and Canada (n = 8, 15%; 0.09, 0.22) (online suppl. Fig. S5). The prevalence score also increased from 1971 to 2021 from −26% (−0.51, −0.02) to a recent 23% (online suppl. Fig. S6). The leave-one-out analysis showed three potential outliers; Aung et al. [2021] (subdivided into three based on race groups), John et al. [2015]; Kallis et al. [1971] (online suppl. Fig. S7A), with most studies being very close to the regression line (online suppl. Fig. S7B). The CE funnel plot showed asymmetry with fewer studies in areas for statistical non-significance (online suppl. Fig. S8A), although Egger’s test showed no small study effect (online suppl. Fig. S8B). We performed a trim and fill analysis, and 11 studies were imputed in the funnel plot based on the bias-corrected overall estimate, and the SMD increased to 30% (0.23, 0.37) (online suppl. Fig. S8C).

Fig. 3.

Forest plot of prevalence of d > 0 among children.

Fig. 3.

Forest plot of prevalence of d > 0 among children.

Close modal

The GRADE assessment scores ranged from four for mean dmft (online suppl. Table S5) and three for untreated caries prevalence. The lowest rating was due to the presence of high publication bias and the presence of high heterogeneity in the reported estimates due to high I2 scores. The high scores were marked high due to the large sample size, systematic random sampling, and samples sufficiently representative of the study population.

This systematic review showed that among racially minoritized children aged 5–11 years, the magnitude of prevalence and severity (mean dmft) of dental caries was higher compared to non-minoritized privileged children. Dental caries among minoritized children has been continuously high for the last 2 decades, with the gap within industrialized high-income countries widening.

Worldwide, untreated dental caries in deciduous teeth was the tenth most prevalent and the fourth most expensive chronic disease to treat condition among children, with prevalence peaks at 6 years of age [Petersen, 2008; Kassebaum et al., 2015]. The global burden of dental caries report shows substantial inequities affecting marginalized and lower socioeconomic status groups and is higher among low- and middle-income countries [Peres et al., 2019; Watt et al., 2019; Wen et al., 2022]. In our systematic review, the distribution of caries was not homogenous and varied across countries, with the highest burden amongst minoritized children from high-income countries. The ethnic (Indigenous) groups of Australia, New Zealand, Brazil, and Canada, minority Asian children in the UK, and black and Hispanic children from the USA have the highest caries burden. In high-income countries, the focus is more towards treating than prevention of dental caries, which is becoming highly technical, specialized care, and highly technological [Watt et al., 2019]. While these interventions continue to benefit the privileged population, the racially minoritized population often has restricted access to high-quality dental care. These findings may also reflect the over-representation of data from high-income countries in this review.

Owing to social, political, and other factors, racially minoritized groups of children also, unfortunately, belong to the lower economic strata. Neoliberal ideologies emphasize profit-driven models and privatization of dental care, causing unequal access to dental services. The implementation of community-based oral health promotion programmes, preventive services, and public health campaigns that are essential for addressing dental health inequities among racially minoritized communities can be limited by insufficient allocation of funds towards public health infrastructure and preventive measures [Jamieson et al., 2020]. The cumulative impacts of racial discrimination pivoted by structural and institutional racist policies and health systems result in further oral health inequities [Bastos et al., 2018; Jamieson et al., 2021]. Evidence shows how racial discrimination has led to distrust in the Western medicine and dental care system, resulting in a lower uptake of services and worse oral health outcomes [Ali et al., 2021]. Biological and genetic differences have often been used as constructs to theorize these inequalities, but racial inequities in dental health are a poignant result of continuing systems of oppression and racism. The authors would like to acknowledge that measuring race/ethnicity could be a proxy measure of racism and highlight that none of the included papers in this review emphasized the effects of racism on reported oral health inequities. There are no reports of the effects of direct racism and dental caries occurrence, and this area is complex and still in its infancy.

Another reason for the increased occurrence of untreated dental caries among racially minoritized children could be the allostatic load. This is the biological “wear and tear” on physiological systems brought on by chronic repeated exposure to stress that causes a release of chemical mediators repeatedly until the physiological system is overloaded, leading to increased susceptibility to disease [Park et al., 2022]. The weathering hypothesis also suggests that racial minoritized populations may experience early health deterioration because of cumulative stress due to adversity and marginalization [Forde et al., 2019]. Both theories support the argument that race is a risk marker for dental caries and long-term, systemic health conditions, such as obesity, diabetes, and hypertension.

It is important to be aware that differences in social group construction will drive the interpretation of dental caries inequities. How race is defined, conceptualized, and differentiated would define the outcomes and conclusions drawn from the outcomes. Race and ethnicity are often interchangeably used despite each having a distinct meaning and conceptual underpinning. Race is a socioculturally constructed categorization that specifies the rules for identifying a group, whereas shared cultural traditions, beliefs, history, celebrations, and language define ethnicity [Ross et al., 2020]. The use of racial/ethnic categories has helped in documenting and monitoring dental health inequities, but these categories are themselves the products of racism. There were many ways of categorizing race, such as the country of origin, country-specific classification system (e.g., the Office of Management and Budget), language, religion, culture, and phenotypic appearance [Selvarajah et al., 2020]. From our review, it is unclear whether dental researchers used the terminologies in their correct context, with most not explaining the effects of race on the dental caries outcome.

This systematic review highlights the available evidence by aggregating data using a meta-analytical approach, providing a unified conclusion. A comprehensive literature search with an extensive grey literature search was conducted to account for unpublished articles, with the earliest publication from the 1960s. Articles were translated from different languages to make the review more comprehensive, and included studies that only diagnosed dental caries using the US Centers for Disease and Control and Prevention criteria [Centers for Disease Control and Prevention, 2022]. High heterogeneity was observed, which can be explained by methodological variation, such as differences in the definition of target and control population, excluding studies diagnosing caries by other methods, geographical location, sample size, time or year of publication, and country of publication. Subgroup analyses were performed to circumvent some degree of heterogeneity, with mean dmft and prevalence of dental caries consistently found to be higher among minoritized children. A high risk of publication bias based on the CE funnel plots was recorded, as minimal studies reported statistical non-significance. This was highly prevalent in high-income countries, such as Australia and the USA, where more papers reporting results with significant differences were reported.

There were some limitations to this systematic review. Our study was restricted to the dmft as a measure of dental caries, and studies with other methods were excluded. The meta-analysis did not include meta-regression analysis to consider the potential confounders, such as sugar consumption, parental socio-economic status, education, and oral hygiene habits etc. But some of these confounding factors were either missing or inconsistent across the included studies, and the validity of conducting a robust meta-regression analysis would be compromised [Ahn and Kang, 2018]. The studies included in the meta-analysis exhibited significant heterogeneity and risk of bias.

Our review does not improve the quality of the available evidence but facilitates identifying aspects that could be improved in future reports. Few studies reported individual “d,” “m,” and “f” components separately, and most failed to report the SD or calculate the sample size or power estimation. Most of the studies were cross-sectional, and additional longitudinal studies would establish whether the progression and prognosis of dental caries differs among racially minoritized groups. The use of race categories within their appropriate contexts is recommended, such as exploring areas of systemic racial or ethnic bias, collecting rich and accurate data for race/ethnicity (e.g., self-reported, open-ended questions) for national surveys, avoiding combining groups into “other” categories when unnecessary and unjustifiably using the white population as the control population.

Our findings suggest an emphasis on improving dental caries for minoritized children. We suggest making small changes at different levels; (1) Individual level: the dentist should strive to understand and respect the cultural background of their patients and be aware of their own implicit bias. It is also important to stay updated on the latest research on racial inequities and cultural competency and adopt a culturally secure approach to clinical practise, such as translated material, a diverse clinical staff, and a welcoming environment for families of ethnic and minoritized backgrounds. (2) Institutional level: more diversity in the dental profession workforce with dentists from racial and ethnic minoritized backgrounds in community dental clinics. Also, offering cultural competence training to dentists to develop a deeper understanding and appreciation of different cultures. (3) Community and school level: promotion and prevention programmes directed towards school children to prevent dental caries (e.g., reduced sugar intake, increased fluoridated toothpaste, sealant programmes). Introducing affordable payment plan options to increase access to services and community-centric, culturally secure dental treatment. The dentist can volunteer at community clinics providing pro bono care and supporting community-based organizations; (4) Structural level: securing more funding for conducting robust, high-quality research to generate knowledge and evidence on racial inequities is imperative. Research can inform targeted intervention and policy development. Government and non-profit organizations, advocacy groups, and community healthcare groups should collectively collaborate to tackle racial inequities. The intersectional forms of inequities, direct effects of personal and systemic racism, distribution of power and continuing impact of colonialism needs to be explored. In conclusion, we would call for global efforts to address the social and political determinants of oral health, and mitigate race-based oral health inequities, whilst prevalence and severity of dental caries amongst school-going children from racially and ethnically minoritized groups remains a global public health concern.

An ethics statement is not applicable because this study is based exclusively on the published literature.

All other authors declare no competing interests.

S.N. is supported by the Research Training Programme Scholarship.

S.N. performed the search, and was the first reviewer for article screening, and for data extraction and quality appraisal. S.S. was the second reviewer for article screening, and for data extraction and quality appraisal. L.M.J. was the third reviewer for data extraction and quality appraisal. The extracted data were used for meta-analyses, and S.N., S.S., and K.K. were responsible for these data used to perform the statistical analysis and wrote the first draft of the manuscript with input from J.B., H.M.C., and D.H. J.B., G.M., and L.M.J. reviewed the manuscript and gave input on the statistical analysis, including having access to summarized data from included studies used for meta-analyses. All authors provided input on the writing of the manuscript.

All data generated or analysed during this study are included in this article. Further enquiries can be directed to the corresponding author.

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