Residential greenness is differentially associated with childhood allergic rhinitis and aeroallergen sensitization in seven birth cohorts
Bibliographic record
Abstract
BACKGROUND: The prevalence of allergic rhinitis is high, but the role of environmental factors remains unclear. We examined cohort-specific and combined associations of residential greenness with allergic rhinitis and aeroallergen sensitization based on individual data from Swedish (BAMSE), Australian (MACS), Dutch (PIAMA), Canadian (CAPPS and SAGE), and German (GINIplus and LISAplus) birth cohorts (n = 13 016). METHODS: Allergic rhinitis (doctor diagnosis/symptoms) and aeroallergen sensitization were assessed in children aged 6-8 years in six cohorts and 10-12 years in five cohorts. Residential greenness was defined as the mean Normalized Difference Vegetation Index (NDVI) in a 500-m buffer around the home address at the time of health assessment. Cohort-specific associations per 0.2 unit increase in NDVI were assessed using logistic regression models and combined in a random-effects meta-analysis. RESULTS: Greenness in a 500-m buffer was positively associated with allergic rhinitis at 6-8 years in BAMSE (odds ratio = 1.42, 95% confidence interval [1.13, 1.79]) and GINI/LISA South (1.69 [1.19, 2.41]) but inversely associated in GINI/LISA North (0.61 [0.36, 1.01]) and PIAMA (0.67 [0.47, 0.95]). Effect estimates in CAPPS and SAGE were also conflicting but not significant (0.63 [0.32, 1.24] and 1.31 [0.81, 2.12], respectively). All meta-analyses were nonsignificant. Results were similar for aeroallergen sensitization at 6-8 years and both outcomes at 10-12 years. Stratification by NO2 concentrations, population density, an urban vs rural marker, and moving did not reveal consistent trends within subgroups. CONCLUSION: Although residential greenness appears to be associated with childhood allergic rhinitis and aeroallergen sensitization, the effect direction varies by location.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.006 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".