The joint association of anxiety, depression and obesity with incident asthma in adults: the HUNT Study
Bibliographic record
Abstract
BACKGROUND: Anxiety or depression symptoms may increase the risk of developing asthma, and their interaction with obesity is not known. We aimed to assess the association of anxiety or depression symptoms and the joint association of these symptoms and obesity with incident asthma. METHODS: We conducted a prospective cohort study of 23 599 adults who were 19-55 years old and free from asthma at baseline in the Norwegian Nord-Trøndelag Health Study. The Hospital Anxiety and Depression Scale was used to measure anxiety or depression symptoms. Obesity was defined as a body mass index≥30.0 kg/m2. Incident asthma was self-reported new cases of asthma during the 11-year follow-up. RESULTS: Having anxiety or depression symptoms was associated with incident asthma [odds ratio (OR) 1.39, 95% confidence interval (CI) 1.09-1.78). Obese participants with anxiety or depression symptoms had a substantially higher risk of incident asthma (OR 2.93, 95% CI 2.20-3.91) than any other group (non-obese participants without anxiety or depression symptoms [reference], non-obese participants with anxiety or depression symptoms (OR 1.20, 95% CI 1.00-1.45) and obese participants without anxiety or depression symptoms (OR 1.47, 95% CI 1.19-1.82)]. The relative excess risk for incident asthma due to interaction between anxiety or depression symptoms and obesity was 1.26 (95% CI 0.39-2.12). CONCLUSIONS: This study suggests that having anxiety or depression symptoms contributes to the development of asthma in adults. The risk of asthma may be further increased by the interaction between anxiety or depression symptoms and obesity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".