Dental divisions: exploring racial inequities of dental caries amongst children
Bibliographic record
Abstract
Abstract Data sources The search strategy involved three sequential stages. Initially, MEDLINE/PubMed was explored for relevant articles, identifying pertinent terms for formal searching. Using the terms ethnic, race, minoritised and dental caries, a strategy was formed and nine databases searched. Finally, hand-searching of reference lists of included articles and sourcing grey literature from relevant government reports, national oral health surveys, and registries which had comparative data for dental caries between racial groups, completed the search. Study selection Studies included were original primary research which reported dental caries and compared racially minoritised children, aged 5–11 years, to similarly aged from national, majority, or privileged populations. Dental caries had to be recorded from a clinical examination which assessed decayed, missing, and filled teeth (dmft) in primary dentitions. Studies were excluded if they used immigration status as a basis of racial status, or they were a case report, case series, in vitro study, or literature review. Data extraction and synthesis After removing duplicates, two independent researchers screened abstracts, prior to extracting critical data following full-text reviews of included articles. Information collected included study and participant characteristics, definitions of race, and dental caries measurement. The authors of studies which had missing data were contacted, whilst those not written in the English language were translated. Methodological quality of each study was independently assessed by two reviewers using a modified version of the Newcastle-Ottawa scale. All studies were included in the review regardless of quality. A narrative overview of all included studies was conducted. Meta-analyses were completed using studies that reported the mean and standard deviation of the caries outcomes in both groups. Caries outcomes included severity (defined as mean dmft) or prevalence (percentage of teeth with untreated dental caries > 0%). Due to anticipated heterogeneity, statistical analyses approaches such as I 2 statistics were used to estimate between-study variability. Additional sub-group analyses were conducted based on country of study and world income index. Contour-enhanced funnel plots and trim-and-fill analysis were completed to explore potential publication bias. Sensitivity analyses were performed to ensure robustness of the findings. Results Seventy-five studies were included from a variety of countries. A higher mean dmft score of 2.30 (0.45, 4.15) and prevalence of decayed teeth ( d > 0) was 23% (95% CI: 16, 31) was noted amongst racially minoritised children compared to privileged children’s populations. Notable disparities were reported in high-income countries, with minoritised children burdening the greatest distribution of caries incidence. The study faced challenges in consistent racial classification and encountered high heterogeneity in its findings, leading to varied GRADE assessment scores. Conclusions The study calls for global, social, and political changes to tackle the substantial disparities in dental caries among minoritised children to achieve oral health equity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".