Associations between parental health, early life factors and asthma, rhinitis and eczema among pre-school children in Chongqing, China
Bibliographic record
Abstract
Purpose: To study associations between parental health and children’s asthma, rhinitis and eczema.Methods: Parents of 3-6 years old children from randomized kindergartens in Chongqing, China answered a questionnaire on parents’ history of asthma/allergies, current symptoms and children’ doctor-diagnosed asthma and rhinitis, wheeze, cough, rhinitis and eczema. Associations were analyzed by multiple logistic regression.Results: Among 4250 children (response rate: 74.5%), 8.4% had doctor-diagnosed asthma (DD asthma); 6.2% doctor-diagnosed allergic rhinitis (DD rhinitis); 20.4% current wheeze; 19.4% cough; 37.9% rhinitis and 13.6% eczema. Among reporting parents (females 70.4%, males 20.6% ), 16.2% were smokers; 47.4% had any current rhinitis; 54.2% cough; 47.8% skin symptoms; 70.5% fatigue and 48.7% headache.Parental asthma or allergy was associated with children’s DD asthma (OR=3.64) and DD rhinitis (OR=4.23). The associations were stronger for paternal asthma or allergy. Children of mothers who were salespersons during pregnancy had more rhinitis (OR=1.49), and children of white-collar worker mothers had more DD (OR=1.49) and DD rhinitis (OR=1.92). Rural children had less DD rhinitis and current rhinitis. Parental current symptoms were associated with wheeze, cough, rhinitis and eczema among the children with OR ranging from 1.37 to 2.28 (all p<0.001).Conclusions: Parental asthma or allergy can be a risk factor for children’s asthma or allergy, especially paternal asthma or allergy. Growing up in rural areas can be beneficial for rhinitis. Mothers’ occupations during pregnancy may influence asthma and rhinitis in offspring. In studies on children’s asthma or allergies, based on parental reporting, parents’ current symptoms may influence the results.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".