ArticleInternational journal of biometeorology2014
Association of allergic rhinitis or asthma with pollen and chemical pollutants in Szeged, Hungary, 1999-2007.
Article in International journal of biometeorology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 13 citations in OpenAlex.
- Identifying key molecular interactions and pathways linking DEHP and its metabolite MEHP to allergic rhinitis: a network toxicology and molecular dynamics study.BMC pharmacology & toxicology · 2026Article
- Respiratory and Related Comorbidities' Role in the Risk of Acute Sinusitis: A 15-Year Longitudinal Clinical Study.Journal of clinical medicine · 2026Article
- A Review of the Respiratory Health Burden Attributable to Short-Term Exposure to Pollen.International journal of environmental research and public health · 2022Review
- Allergenic pollen production across a large city for common ragweed (Landscape and urban planning · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The effect of biological (pollen) and chemical air pollutants on respiratory hospital admissions for the Szeged region in Southern Hungary is analysed. A 9-year (1999-2007) database includes--besides daily number of respiratory hospital admissions--daily mean concentrations of CO, PM10, NO, NO2, O3 and SO2. Two pollen variables (Ambrosia and total pollen excluding Ambrosia) are also included. The analysis was performed for patients with chronic respiratory complaints (allergic rhinitis or asthma bronchiale) for two age categories (adults and the elderly) of males and females. Factor analysis was performed to clarify the relative importance of the pollutant variables affecting respiratory complaints. Using selected low and high quantiles corresponding to probability distributions of respiratory hospital admissions, averages of two data sets of each air pollutant variable were evaluated. Elements of these data sets were chosen according to whether actual daily patient numbers were below or above their quantile value. A nonparametric regression technique was applied to discriminate between extreme and non-extreme numbers of respiratory admissions using pollen and chemical pollutants as explanatory variables. The strongest correlations between extreme patient numbers and pollutants can be observed during the pollen season of Ambrosia, while the pollen-free period exhibits the weakest relationships. The elderly group with asthma bronchiale is characterised by lower correlations between extreme patient numbers and pollutants compared to adults and allergic rhinitis, respectively. The ratio of the number of correct decisions on the exceedance of a quantile resulted in similar conclusions as those obtained by using multiple correlations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.