A scoping review on the association between early childhood caries and life on land: The Sustainable Development Goal 15
Bibliographic record
Abstract
BACKGROUND: The Sustainable Development Goal 15 (SDG15) deals with protecting, restoring, and promoting the sustainable use of terrestrial ecosystems, sustainably managing forests, halting and reversing land degradation, combating desertification and halting biodiversity loss. The purpose of this scoping review was to map the current evidence on the association between SDG 15 and Early Childhood Caries (ECC). METHODS: This scoping review was reported in accordance with the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) guidelines. Formal literature searches were conducted in PubMed, Web of Science, and Scopus in March 2023 using key search terms. Studies with the criteria (in English, with full text available, addressing component of life on land, focusing on dental caries in humans, with results that can be extrapolated to control ECC in children less than 6 years of age) were included. Retrieved papers were summarised and a conceptual framework developed regarding the postulated link between SDG15 and ECC. RESULTS: Two publications met the inclusion criteria. Both publications were ecological studies relating environmental findings to aggregated health data at the area level. One study concluded that the eco-hydrogeological environment was associated with human health, including caries. The other reported that excessive calcium was associated with the presence of compounds increasing groundwater acidity that had an impact on human health, including caries. The two ecological studies were linked to SDG 15.1. It is also plausible that SDG 15.2 and SDG 15.3 may reduce the risk for food insecurity, unemployment, gender inequality, zoonotic infections, conflict and migration; while SDG 15.4 may improve access to medicinal plants such as anticariogenic chewing sticks and reduction in the consumption of cariogenic diets. CONCLUSIONS: There are currently no studies to support an association between ECC and SDG15 although there are multiple plausible pathways for such an association that can be explored. There is also the possibility of synergistic actions between the elements of soil, water and air in ways that differentially affect the risk of ECC. Studies on the direct link between the SDG15 and ECC are needed. These studies will require the use of innovative research approaches.
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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 | 0.020 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".