What is the impact of stress on the development of molar incisor hypomineralization (MIH): a systematic review
Bibliographic record
Abstract
Molar Incisor Hypomineralization (MIH) is a developmental enamel defect that affects permanent first molars (PFMs) and incisors, leading to caries and early tooth loss. This systematic review investigates the literature for the relationship between stress-related factors and the occurrence of MIH. A comprehensive literature search was conducted across PubMed, Cochrane, Scopus, Google Scholar, and BASE. Articles were screened and data extracted using the Rayyan platform for systematic reviews. The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Six-studies were included, five examined maternal stress during pregnancy while one on stress experienced during early childhood. Out of them, five reported a significant association between stress and MIH. Given the significant variability in stress assessment methods across studies, we were able to include only two studies in the meta-analysis. Although not statistically significant, the meta-analysis showed a tendency for increased odds of MIH in the presence of stress, with an overall odds ratio of 1.46 (95% CI: 0.66-3.22). These findings suggest a potential association between psychological stress and MIH. However, further research is needed to confirm these results and elucidate the mechanisms involved. Addressing current research limitations will improve study reliability and inform preventive strategies to reduce maternal and early childhood stress, potentially mitigating MIH prevalence.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.010 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".