Association of Abnormal Body Weight and Allergic Rhinitis—A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Objective Allergic rhinitis (AR) is a prevalent inflammatory condition of the nasal mucosa, with significant burden worldwide. While studies have demonstrated a relationship between body mass index (BMI) and other atopic diseases, its association with AR is uncertain. This study aims to clarify the association between non‐normal BMI and AR. Design According to Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) recommendations, independent authors screened studies for eligibility, extracted data and assessed bias of included studies using the Newcastle–Ottawa scale and the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. A random‐effects meta‐analysis was used to pool maximally covariate‐adjusted estimates. Additional subgroup and bias analyses were performed. Data Sources PubMed, Embase, Cochrane Library, SCOPUS and CINAHL were searched from inception to 14 January, 2024. Eligibility Criteria Observational studies investigating the association between non‐normal BMI and AR in both children and adults. Results We included 32 articles comprising 2,008,835 participants. The risk of bias was low (N = 20) or moderate (N = 12) and GRADE certainty of evidence was very low to low. Pooled cross‐sectional analyses indicated that obese children (OR = 0.99, 95% CI = 0.96–1.03, I2 = 0%), obese adults (OR = 1.11, 95% CI = 0.92–1.33, I2 = 73%), overweight children (OR = 1.02, 95% CI = 0.98–1.06, I2 = 35%), and overweight adults (OR = 1.13, 95% CI = 0.90–1.40, I2 = 0%) showed similar odds of AR compared to controls. Additionally, longitudinal analyses did not identify any evidence for an association between overweight (OR = 1.03, 95% CI = 0.85–1.24, I2 = 29%) or underweight (OR = 1.09, 95% CI = 0.77–1.54, I2 = 72%) children and AR risk. These results remained largely robust across various subgroups and sensitivity assessments. Conclusion Abnormal BMI may not be associated with AR. This study adds to the expanding literature on the association between non‐normal BMI and atopic diseases. Further prospective studies are needed to explore the longitudinal relationship between BMI and AR and the effect of weight loss interventions on AR, given the limits of existing literature. Trial Registration PROSPERO CRD42024503589
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 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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.035 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".