Dental Caries in Relation to Type of Disability: A Cross-sectional Study of Disabled Children in Tehran, Iran
Bibliographic record
Abstract
Objectives Literature has reported high caries prevalence and unmet dental treatment needs among disabled individuals. This study was carried out to assess the oral health condition of disabled students in relation to age, gender, and type of disability in Tehran, Iran. Methods The study involved 1,170 disabled students aged 6 to 20 years, each with one or more of the following disabilities: physical retardation (PR), hearing impairment (HI), visual impairment (VI), mental retardation (MR), and autism spectrum disorder (ASD). The mean decayed, missing, and filled teeth index was used as an oral health indicator (dmft for children aged 6-12 years, and DMFT for children older than 9 years). Mann-Whitney and Kruskal-Wallis tests at significant level of 0.05 were conducted for comparisons. Results Mental retardation (MR) was the most prevalent disability (59.4%). The decayed component constituted the largest part of the mean dmft (82%) and DMFT (75%) indices in all age groups. Girls had significantly higher DMFT scores compared to boys (P < 0.001). Among the different disabilities, children with HI had the highest dmft score (mean ± SD = 2.17 ± 2.86), while those with MR had the highest DMFT score (mean ± SD = 3.76 ± 3.83). Additionally, the caries-free ratio was significantly higher among VI students in the 9-12 years (40.5%) and older than 13 years (38.8%) age groups. Conclusion The high prevalence of untreated dental caries, particularly among those with HI and MR, points to significant unmet treatment needs and emphasizes the importance of regular dental check-ups and access to dental care. These results underscore the critical need for improved oral health services and preventive programs tailored to the specific needs of disabled students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 source (direct Gemma or distilled Codex), 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".