It’s Not Just About Baby Teeth: Preventing Early Childhood Caries
Bibliographic record
Abstract
Early Childhood Caries (ECC) is a serious disease that is about much more than cavities on baby teeth. In Canada, it is a growing public health problem with adverse long-term effects on children's physical, emotional and intellectual well-being. The failure to invest in preventive care has resulted in reactive, rather than proactive, measures against this disease. These measures are expensive and a needless drain on costs in the public health-care system. Children with severe ECC end up in hospital; in fact, in Canada, this disease is the most common reason children undergo day surgery. From 2010 to 2012, one in 100 children under age five required day surgery for ECC, with approximately 19,000 of these surgeries performed each year on children under age six. Canadian hospital costs for ECC day surgery in children aged one to five ranged from $1,271 to $1,963 per child, totalling $21.2 million between 2010 and 2012. Children from low-income families, along with aboriginal, immigrant and refugee children are disproportionately affected by dental disease, with between 50 per cent and 90 per cent of suffering from some form of ECC. This compares to an average of 57 per cent of children affected in the general population. A recent Alberta study indicates that when municipalities cease fluoridating their water supplies, children suffer increased levels of tooth decay. This has reignited the discussion around whether municipalities should add fluoride to the drinking water, or reinstate it in places where the water used to be fluoridated. While fluoridation can be an effective prevention strategy, this study also shows that fluoride alone is not enough. To reduce the costs and developmental consequences associated with severe ECC and improve well-being, oral health policies focused on disease prevention and health promotion are still necessary. This briefing paper provides background on the etiology, risk factors and prevalence of ECC in Canada to provide scope for the magnitude of this preventable disease in children. To address the avoidable socioeconomic costs, three areas require policy development. First is the need for increased public education and access to ECC prevention services for at-risk populations. Parents need to know they should reduce their children’s intake of sweet drinks, and avoid filling bottles with sugar water, juice or soft drinks, especially at night. They should also clean an infant’s gums with a soft toothbrush or cloth and water starting at birth. When the baby’s first tooth erupts, parents should commence daily brushing with toothpaste and book a first dental visit. Second is the need to empower health-care professionals to integrate ECC prevention in their early visits with parents of young children. Such visits are more common in family medicine, and these primary care providers can play a critical role in educating parents and promoting children’s oral health. Curriculum and continuing education for these health professions should be enhanced to emphasize ECC’s long-term health effects. Third, government should invest in preventive oral health services for children rather than relying on emergency dental care. Children should have access to early preventive dental services to instill in them habits for lifetime oral health. Provinces without universal public funding for children’s preventive dental health should remove the access barriers that children without dental insurance face.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".