The social environment and dental caries development: A comprehensive investigation of potential mechanisms
Bibliographic record
Abstract
Introduction: Despite considerable prevention efforts, dental caries remains the most prevalent oral disease worldwide, especially among people with lower socioeconomic positions, resulting in significant health inequities. This is partially attributable to overlooking the health impacts of the social environment. Various dimensions of the social environment may affect oral health, either independently or interdependently. However, previous studies have focused on separate social dimensions. Moreover, the underlying biological mechanisms linking the social environment to dental caries remain unclear. This thesis investigates the direct and indirect mechanisms through which the social environment influences dental caries development.Methods: Data for this thesis are drawn from the QUALITY Cohort, a population-based study conducted in Montreal, Sherbrooke, and Quebec City. A total of 630 children of Western European ancestry aged 8-10 years, with at least one biological parent with obesity, were recruited, together with both biological parents, for baseline assessment between 2005-2008. Follow-ups were conducted between 2007-2010 and 2012-2015. A wide range of information was collected at environmental, family, and individual levels.In Manuscript I, I identified distinct typologies of the neighbourhood social environment at baseline and estimated their associations with dental caries risk. In Manuscript II, I examined the diversity and composition of oral microbiota from baseline to the second follow-up and estimated the association between the diversity of oral microbiota in childhood and dental caries risk in adolescence. Based on findings from the previous two manuscripts, in Manuscript III, I investigated both the multiplicative and additive interactions of the neighbourhood social environment and diversity of oral microbiota in childhood and their associations with dental caries risk in adolescence.Results: Three socio-environmental typologies were identified: Type 1 (high social disorder and social deprivation, but low material deprivation), Type 2 (median social disorder, social deprivation, and material deprivation), and Type 3 (low social disorder and social deprivation, but high material deprivation). Compared to children living in Type 1 neighbourhoods, those in either Type 2 or Type 3 neighbourhoods had a lower risk of developing dental caries. Additionally, among children living in Type 1 neighbourhoods, a positive association was observed between the diversity of oral microbiota in childhood and dental caries risk in adolescence. This relationship was further strengthened in Type 2 and 3 neighbourhoods. The interaction between the neighbourhood social environment and the diversity of oral microbiota was super-multiplicative and super-additive, indicating the social environment may influence children’s risk of dental caries through interactions with oral microbiota.Conclusion: This thesis provides evidence that residing in neighbourhoods with favourable social environments may contribute to the prevention of dental caries. Furthermore, it suggests that the childhood social environment may influence children’s susceptibility to dental caries by interacting with the diversity of oral microbiota. Interventions for preventing dental caries among the pediatric population should consider improving the neighbourhood social environment. Future research with diverse populations and extended follow-up periods is necessary to validate these findings
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".