Maternal Mental Disorders and Pediatric Infectious Diseases
Bibliographic record
Abstract
BACKGROUND: Maternal stress and depression are associated with infections in offspring, but there is a paucity of data for other mental disorders. METHODS: We conducted a retrospective cohort study of 832,290 children born between 2006 and 2016 in hospitals of Quebec, Canada. We identified maternal mental disorders before and during pregnancy, and admissions for otitis media, pneumonia, infectious enteritis and other infections in children before 13 years of age. We used Cox proportional hazards regression to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for the association between maternal mental disorders and the risk of pediatric infectious diseases, adjusted for maternal age, comorbidity, socioeconomic disadvantage, and other confounders. RESULTS: The incidence of pediatric infection hospitalization was higher for maternal mental disorders compared with no disorder (66.1 vs. 41.1 cases per 1000 person-years). Maternal mental disorders were associated with 1.38 times the risk of otitis media (95% CI: 1.35-1.42), 1.89 times the risk of bronchitis (95% CI: 1.68-2.12), and 1.65 times the risk of infectious enteritis in offspring (95% CI: 1.57-1.74). Stress and anxiety disorders (HR 1.49, 95% CI: 1.46-1.53) and personality disorders (HR 1.55, 95% CI: 1.49-1.61) were more strongly associated with the risk of pediatric infection hospitalization than other maternal mental disorders. Associations were prominent in the first year of life and weakened with age. CONCLUSIONS: Maternal mental disorders are risk factors for infectious disease hospitalization in offspring. Women with mental disorders may benefit from psychosocial support to reduce the risk of serious infections in their children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".