The Biology of Social Adversity Applied to Oral Health
Bibliographic record
Abstract
Biological embodiment is a concept derived from Engel's biopsychosocial model to health, theorized as the process by which adverse social exposures trigger neuroendocrine and immune responses, leading to disease and/or increased disease susceptibility. This critical review discusses the biopsychosocial model as applied to oral health and its relevance to oral health policy while deciphering some of the pathobiological processes underlying social adversity. In periodontal disease, for example, such processes can occur via the activation of the hypothalamic-pituitary-adrenal axis and the consequent release of the chronic stress hormone cortisol. The latter contributes to a proinflammatory immune state that increases the risk for periodontal inflammation. Recent research shows that cortisol relates to an elevated oral inflammatory load, demonstrated as hyperactive neutrophils that are pivotal to periodontal tissue damage. Consistent with the biopsychosocial model, this relationship is amplified in those of lower income and higher financial stress. Similarly, among children from lower socioeconomic backgrounds, cortisol is linked to a higher cariogenic bacterial load. Such findings implicate the stress pathway as key in the oral pathogenic process, particularly under social/socioeconomic adversity. Collectively, this work emphasizes the importance of addressing social factors in alleviating oral disease burden and reducing the social gaps therein.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".