Maternal Depressive Symptoms across Early Childhood and Asthma in School Children: Findings from a Longitudinal Australian Population Based Study
Bibliographic record
Abstract
There is a growing body of evidence attesting to links between early life exposure to stress and childhood asthma. However, available evidence is largely based on small, genetically high risk samples. The aim of this study was to explore the associations between the course of maternal depressive symptoms across early childhood and childhood asthma in a nationally representative longitudinal cohort study of Australian children. Participants were 4164 children and their biological mothers from the Longitudinal Study of Australian Children. Latent class analysis identified three trajectories of maternal depressive symptoms across four biennial waves from the first postnatal year to when children were 6-7 years: minimal symptoms (74.6%), sub-clinical symptoms (20.8%), and persistent and increasing high symptoms (4.6%). Logistic regression analyses revealed that childhood asthma at age 6-7 years was associated with persistent and increasing high depressive symptoms after accounting for known risk factors including smoking during pregnancy and maternal history of asthma (adjusted OR 2.36, 95% CI 1.61-3.45), p.001). Our findings from a nationally representative sample of Australian children provide empirical support for a relationship between maternal depressive symptoms across the early childhood period and childhood asthma. The burden of disease from childhood asthma may be reduced by strengthening efforts to promote maternal mental health in the early years of parenting.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".