Early family socioeconomic status and asthma-related outcomes in school-aged children: Results from seven birth cohort studies
Bibliographic record
Abstract
OBJECTIVE: To examine the associations between maternal education and household income during early childhood with asthma-related outcomes in children aged 9-12 years in the UK, the Netherlands, Sweden, Australia, the USA and Canada. METHODS: Data on 31 210 children were obtained from 7 prospective birth cohort studies across six countries. Asthma-related outcomes included ever asthma, wheezing/asthma attacks and medication control for asthma. Relative social inequalities were estimated using pooled risk ratios (RRs) adjusted for potential confounders (child age, sex, mother ethnic background and maternal age) for maternal education and household income. The Slope Index of Inequality (SII) was calculated for each cohort to evaluate absolute social inequalities. RESULTS: Ever asthma prevalence ranged from 8.3% (Netherlands) to 29.1% (Australia). Wheezing/asthma attacks prevalence ranged from 3.9% (Quebec) to 16.8% (USA). Pooled RRs for low (vs high) maternal education and low (vs high) household income were: ever asthma (education 1.24, 95% CI 1.13 to 1.37; income 1.28, 95% CI 1.15 to 1.43), wheezing/asthma attacks (education 1.14, 95% CI 0.97 to 1.35; income 1.22, 95% CI 1.03 to 1.44) and asthma with medication control (education 1.16, 95% CI 0.97 to 1.40; income 1.25, 95% CI 1.01 to 1.55). SIIs supported the lower risk for children with more highly educated mothers and those from higher-income households in most cohorts, with few exceptions. CONCLUSIONS: Social inequalities by household income on the risk of ever asthma, wheezing/asthma attacks, and medication control for asthma were evident; the associations were attenuated for maternal education. These findings support the need for prevention policies to address the relatively high risks of respiratory morbidity in children in families with low socioeconomic status.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".