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Record W3105826821 · doi:10.1186/s13223-020-00495-1

Prevalence of allergic rhinitis, related comorbidities and risk factors in schoolchildren

2020· article· en· W3105826821 on OpenAlexvenueno aff
Mónika Sultész, Alpár Horváth, Dávid Molnár, Gábor Katona, G Mezei, Andor Hirschberg, Gabriella Gálffy

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2020
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAtopyAsthmaAllergyEpidemiologyFamily historyPediatricsInternal medicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The study aimed to determine the prevalence and risk factors of allergic rhinitis and related comorbidities in school-age children in Budapest, capital of Hungary. Data and epidemiological studies on this disease are still limited. METHODS: A cross sectional study was conducted in 21 representative and randomly selected primary schools in 2019. International Study of Asthma and Allergies in Childhood-based questionnaires (n = 6869) inquiring about prevalence and related risk factors of allergic rhinitis were distributed to all parents. The data were characterised with standard descriptive statistics: frequencies (percentages) and means for categorical and quantitative data, respectively. RESULTS: 3836 of the questionnaires (1857 M/1979F) were completed. The prevalence of current allergic rhinitis was 29.3% (1043), physician-diagnosed allergic rhinitis was 9.7% (373), cumulative allergic rhinitis was 36.2% (1289) and current allergic rhinoconjunctivitis was 16.2% (577). The presence of physician diagnosed atopic disease-asthma (p < 0.0001, OR = 4.398, 95% CI 3.356-5.807), food allergy (p < 0.0001, OR = 2.594, 95% CI 1.995-3.378), and eczema (p < 0.0001, OR = 1.899, 95% CI 1.568-2.300)-were significantly related to an increased risk of cumulative allergic rhinitis. Significant factors associated with allergic rhinitis include male gender (p < 0.0001), family history of atopy (p < 0.0001), frequent upper respiratory tract infections (p < 0.0001), tonsillectomy (p = 0.0054), antibiotics given in the first year of life (p < 0.0001), paracetamol given in the first year of life (p = 0.0038), long-lasting common infections caused by viruses and/or bacteria before the appearance of the allergy (p < 0.0001), consumption of drinks containing preservatives or colourants (p = 0.0023), duration of living in Budapest (p = 0.0386), smoking at home (p = 0.0218), smoking at home in the first year of life (p = 0.0048), birds at home (p = 0.0119), birds at home in the first year of life (p = 0.0052), visible mould in the bedroom (p = 0.0139), featherbedding (p = 0.0126), frequent or constant heavy-vehicle traffic (p = 0.0039), living in a weedy area (p < 0.0001) and living in the vicinity of an air-polluting factory or mine (p = 0.0128). CONCLUSIONS: The prevalence of allergic rhinoconjunctivitis in 6-12-year-old children in Budapest is higher than reported for most of the surrounding European countries. While asthma (OR = 4.398) is the most significant comorbidity, environmental factors such as birds at home in the first year of life (OR = 2.394) and living in a weedy area (OR = 1.640) seem to be the most important factors associated with AR. Strategies for preventive measures should be implemented. TRIAL REGISTRATION NUMBER: KUT-19/2019. The study was approved by the Ethics Committee at Heim Pál National Pediatric Institute.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.076
Threshold uncertainty score0.596

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.280
Teacher spread0.257 · 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 teacher head, 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

Citations62
Published2020
Admission routes1
Has abstractyes

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