Association of maternal diabetes and child asthma
Bibliographic record
Abstract
BACKGROUND: Perinatal programming is an emerging theory for the fetal origins of chronic disease. Maternal asthma and environmental tobacco smoke (ETS) are two of the best-known triggers for the perinatal programming of asthma, while the potential role of maternal diabetes has not been widely studied. OBJECTIVE: To determine if maternal diabetes is associated with child asthma, and if so, whether it modifies the effects of ETS exposure and maternal asthma. METHODS: We studied 3,574 Canadian children, aged 7-8 years, enrolled in a population-based birth cohort. Standardized questionnaires were completed by the children's parents, and data were analyzed by multivariable logistic regression. RESULTS: Asthma was reported in 442 children (12.4%). Compared to those without asthma, asthmatic children were more likely to have mothers (P = 0.003), but not fathers (P = 0.89), with diabetes. Among children without maternal history of diabetes, the likelihood of child asthma was 1.4-fold higher in those exposed to ETS (adjusted odds ratio, 1.40; 95% confidence interval, 1.13-1.73), and 3.6-fold higher in those with maternal asthma (3.59; 2.71-4.76). Among children born to diabetic mothers, these risks were amplified to 5.7-fold (5.68; 1.18-27.37) and 11.3-fold (11.30; 2.26-56.38), respectively. In the absence of maternal asthma or ETS, maternal diabetes was not associated with child asthma (0.65, 0.16-2.56). CONCLUSION: Our findings suggest that maternal diabetes may contribute to the perinatal programming of child asthma by amplifying the detrimental effects of ETS exposure and maternal asthma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".