Trends and regional distribution of outpatient claims for asthma, 2009–2016, Germany
Bibliographic record
Abstract
OBJECTIVE: To investigate asthma morbidity in Germany by calculating current prevalence, examining its temporal and spatial trends and estimating the total number of asthmatics in Germany and calculating age-, sex- and residence-specific risk. METHODS: . We assessed the risk of asthma by sex, age, type of residence (rural versus urban) and federal state (East versus West) using a multilevel parametric survival regression. FINDINGS: < 0.0001), and identified local spatial clusters with higher levels of prevalence. Living in the western (versus eastern) federal states and living in densely populated large urban municipalities (versus rural area) were independently associated with an increased risk of asthma, with hazard ratios of 1.33 (95% CI: 1.32-1.34) and 1.32 (95% CI: 1.31-1.32), respectively. CONCLUSION: Our insights into the spatial distribution of asthma morbidity may inform public health interventions, including region-specific prevention programmes and control.
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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".