The association of early-life household endotoxin exposure with asthma, recurrent wheeze, and allergic sensitization in Canadian children 3 years of age
Bibliographic record
Abstract
Asthma and allergies are the leading chronic illnesses among children in Canada, causing a significant burden on healthcare systems and negatively impacting the quality of life of children and their families. Currently, the association between asthma, wheeze, and atopy development and early-life exposure to endotoxin is not fully understood. Data from the CHILD Cohort Study were analyzed using multivariate logistic regression modelling to determine whether an association exists between household early-life endotoxin exposure measured in house dust and asthma, wheeze, and allergy development at 3 years of age. The models were adjusted for covariates relating to the child’s home environment, demographics and socioeconomic status. Those with higher household endotoxin concentrations showed lower odds of allergic sensitization at 3 years of age (OR 0.49, p=0.07 and OR 0.54, p=0.11) than those with the lowest household exposure. Sex stratification found that this relationship was specific to boys. No relationship was found between endotoxin exposure and recurrent wheeze at 3 years of age. Girls in homes with the highest exposure had lower odds of developing asthma by age 3 (p=0.10). These findings suggest endotoxin exposure in early life may protect against allergy at age 3 in Canadian children, particularly boys. Endotoxin is a measure of gram-negative bacteria but may be associated with the presence of ‘good’ microbes in the home environment as well. These findings are consistent with the hygiene hypothesis and encourage more research on early-life microbiome abundance and diversity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".