Prevalence and Risk Factors for ECC Among Preschool Children from India along with the Need of its Own CRA Tool- A Systematic Review
Bibliographic record
Abstract
Introduction: Caries in the deciduous dentition of children under six years of age is termed as early childhood caries (ECC). ECC is prevalent among Indian children and identifying modifiable risk factors is important for prevention. This systematic review was undertaken to describe the burden of ECC in India, its prevalence, associated risk factors along with its repercussions on childhood health. Materials and Methods: A search was conducted for published Indian studies on ECC through electronic databases and complemented with hand search. The protocol for the present systematic review was registered at PROSPERO (Ref No.CRD42022306234)Care was taken to include studies which could represent all parts of India- Central, North, South, East and West. Included papers were reviewed for prevalence of ECC and reported risk factors. Results: Overall 37 studies on ECC in India were identified relating to prevalence, 11 reported risk factors and two reported on the association between severe ECC and nutritional health and well-being. The prevalence of ECC in India in these studies varied from16% to 92.2%. This systematic review revealed that ECC is prevalent among Indian children and highlights the need of preventive intervention and early risk assessment by its own caries risk assessment (CRA) tool. Occurrence seems to be firmly connected with age, snacking frequency, feeding and oral hygiene habits and with social determinants of health including parental education level, low socioeconomic status and number of siblings.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".