Greenness and Allergies: Evidence of Differential Associations in Two Areas in Germany
Bibliographic record
Abstract
Background: Positive effects of green spaces and greenness on health are increasingly reported. However, studies on allergic outcomes remain limited and conflicting. Aim: We examined whether residential greenness is associated with childhood prevalences of doctor diagnosed allergic rhinitis, eyes and nose symptoms and aeroallergen sensitization using two birth cohorts (GINIplus and LISAplus) followed from birth to 10 years in two areas in Germany. Methods: Reports of doctor diagnosed allergic rhinitis (3-10 years) and eyes and nose symptoms (4, 6 and 10 years) were obtained from parent-completed questionnaires (N=5803). Aeroallergen sensitization was also assessed (6 and 10 years, N=3223). Mean residential greenness in a 500m buffer around the 10 year home addresses was defined using the Normalized Difference Vegetation Index, a green biomass density indicator. Longitudinal associations were assessed per study area using generalized estimating equations adjusted for host and environmental covariates. Results: Risk estimates were elevated in the urban GINI/LISA South area (odds ratio:1.16 [95% confidence intervals: 0.99, 1.36], 1.15 [1.01, 1.31] and 1.06 [0.94, 1.20] per interquartile range increase in greenness for doctor diagnosed allergic rhinitis, eyes and nose symptoms and aeroallergen sensitization, respectively). In contrast, risk estimates were significantly below one for these same outcomes in the rural GINI/LISA North area (0.75 [0.60, 0.93], 0.71 [0.56, 0.89] and 0.78 [0.65, 0.94], respectively). Area-specific associations were similar across buffer sizes (800m-3000m) and addresses (birth and 6 years), slightly stronger among never-movers, and remained heterogeneous after air pollution and population density stratification. Conclusions: Despite identical study designs and statistical modeling, greenness was differentially associated with allergic outcomes in two German study areas. Existing and future single-area studies should be interpreted with caution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".