A scoping review on the associations between early childhood caries and sustainable cities and communities using the sustainable development goal 11 framework
Bibliographic record
Abstract
BACKGROUND: Early childhood caries (ECC) is a multifactorial disease in which environmental factors could play a role. The purpose of this scoping review was to map the published literature that assessed the association between the Sustainable Development Goal (SDG) 11, which tried to make cities and human settlements safe, inclusive, resilient and sustainable, and ECC. METHODS: This scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. In July 2023, a search was conducted in PubMed, Web of Science, and Scopus using tailored search terms related to housing, urbanization, waste management practices, and ECC. Studies that solely examined ECC prevalence without reference to SDG11 goals were excluded. Of those that met the inclusion criteria, a summary highlighting the countries and regions where the studies were conducted, the study designs employed, and the findings were done. In addition, the studies were also linked to relevant SDG11 targets. RESULTS: Ten studies met the inclusion criteria with none from the African Region. Six studies assessed the association between housing and ECC, with findings suggesting that children whose parents owned a house had lower ECC prevalence and severity. Other house related parameters explored were size, number of rooms, cost and building materials used. The only study on the relationship between the prevalence of ECC and waste management modalities at the household showed no statistically significant association. Five studies identified a relationship between urbanization and ECC (urbanization, size, and remoteness of the residential) with results suggesting that there was no significant link between ECC and urbanization in high-income countries contrary to observations in low and middle-income countries. No study assessed the relationship between living in slums, natural disasters and ECC. We identified links between ECC and SDG11.1 and SDG 11.3. The analysis of the findings suggests a plausible link between ECC and SDG11C (Supporting least developed countries to build resilient buildings). CONCLUSION: There are few studies identifying links between ECC and SDG11, with the findings suggesting the possible differences in the impact of urbanization on ECC by country income-level and home ownership as a protective factor from ECC. Further research is needed to explore measures of sustainable cities and their links with ECC within the context of the SDG11.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".