Assessing the Impact of Climate Change on Early Childhood Caries Within the Framework of Sustainable Developmental Goal 13: A Scoping Review
Bibliographic record
Abstract
Climate change, a significant factor in global health disparities, has been linked to numerous health issues, including oral health disorders such as dental caries and enamel hypoplasia. Sustainable Developmental Goal 13 (SDG 13) accentuates immediate action to battle climatic changes and their complications. This scoping review aimed to explore the existing evidence in the literature linking SDG 13 with Early Childhood Caries (ECC). The review was carried out following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A rigorous search was done during the month of May 2024 using databases PubMed, Web of Science, Scopus, and Google Scholar with search MeSH terms related to climate change, Early Childhood Caries (ECC), and Sustainable Developmental Goal (SDG). Publications or abstracts were included only in English from 2015 onwards, with no restrictions on the type of study. A summary of the eligible studies was compiled, highlighting the countries where the research was conducted, the type of study designs used, the region, study aims, and key findings. Additionally, the study results were analyzed to determine whether SDG 13 was addressed. The initial search provided 74 articles, of which 51 were duplicates, yielding 23 for screening. After applying the eligibility criteria, seven studies were finally reviewed. Two of the seven studies included were from the African continent (Kenya and Nigeria), and one was a multi-centric study involving various continents, Africa (Nigeria & Kenya), Asia (Saudi Arabia, Indonesia), and America (Canada, Brazil). Two other studies were conducted in the UK, China, and India, while one was from the USA and focused on how climate change impacts dental caries. Only three studies were found to be addressing SDG 13. The review established a plausible link between ECC and climate change factors, addressing the need to incorporate sustainable developmental strategies and eco-friendly preventive measures in pediatric dentistry.
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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 | 0.017 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".