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Record W2971501349 · doi:10.1186/s13223-019-0365-y

Shared prenatal impacts among childhood asthma, allergic rhinitis and atopic dermatitis: a population-based study

2019· article· en· W2971501349 on OpenAlexvenueno aff
Ching‐Heng Lin, Jiun-Long Wang, Hsin‐Hua Chen, Jeng‐Yuan Hsu, Wen‐Cheng Chao

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2019
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
FundersNational Health Insurance AdministrationTaichung Veterans General Hospital
KeywordsAsthmaMedicineAtopic dermatitisOdds ratioConfidence intervalPediatricsPopulationLogistic regressionPregnancyCohort studyDemographyEnvironmental healthInternal medicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Increasing prevalence of childhood allergic diseases including asthma is a global health concern, and we aimed to investigate prenatal risk factors for childhood asthma and to address the potential shared prenatal impacts among childhood asthma, allergic rhinitis (AR) and atopic dermatitis (AD). METHODS: We used two claim databases, including Taiwan Birth Cohort Study (TBCS) and National Health Insurance Research Database (NHIRD), to identify independent paired mother-child data (mother-child dyads) between 2006 and 2009. The association between prenatal factors and asthma was determined by calculating adjusted odds ratio (aOR) with 95% confidence interval (CI) using conditional logistic regression analysis. RESULTS: A total of 628,878 mother-child dyads were included, and 43,915 (6.98%) of children developed asthma prior to age 6. We found that male gender (aOR 1.50, 95% CI 1.47-1.53), maternal asthma (aOR 1.80, 95% CI 1.71-1.89), maternal AR (aOR 1.33, 95% CI 1.30-1.37), preterm birth (aOR 1.32, 95% CI 1.27-1.37), low birth weight (aOR 1.14, 95% CI 1.10-1.19) and cesarean section (aOR 1.10, 95% CI 1.08-1.13) were independent predictors for childhood asthma. A high urbanization level and a low number of older siblings were associated with asthma in a dose-response manner. Notably, we identified that the association between maternal asthma and childhood asthma (aOR 1.80, 95% CI 1.71-1.89) was stronger compared with those between maternal asthma and childhood AR (aOR 1.67, 95% CI 1.50-1.87) as well as childhood AD (aOR 1.31, 95% CI 1.22-1.40). Similarly, the association between maternal AR and childhood AR (aOR 1.62, 95% CI 1.53-1.72) was higher than those between maternal AR and childhood asthma (aOR 1.33, 95% CI 1.30-1.37) as well as childhood AD (aOR 1.35, 95% CI 1.31-1.40). Furthermore, the number of maternal allergic diseases was associated with the three childhood allergic diseases in a dose-response manner. CONCLUSIONS: In conclusion, this population-based study provided evidence of prenatal impacts on childhood asthma and demonstrated the shared maternal impacts among childhood asthma, AR, and AD. These findings highlight the shared prenatal impacts among allergic diseases, and studies are warranted to address the pivotal pathway in allergic diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.283
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2019
Admission routes1
Has abstractyes

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