Physical activity and lung function decline in adults with asthma: The HUNT Study
Bibliographic record
Abstract
ABSTRACT Background and objective People with asthma may seek advice about physical activity. However, the benefits of leisure time physical activity on lung function are unclear. We investigated the association between leisure time physical activity and lung function decline in adults with asthma. Methods In a population‐based cohort study in Norway, we used multiple linear regressions to estimate the annual mean decline in lung function (and 95% CI) in 1329 people with asthma over a mean follow‐up of 11.6 years. The durations of light and hard physical activity per week in the last year were collected by questionnaire. Inactive participants did not report any light or hard activity, while active participants reported light or hard activity. Results The mean decline in forced expiratory volume in 1 s (FEV1 ) was 37 mL/year among inactive participants and 32 mL/year in active participants (difference: −5 mL/year (95% CI: −13 to 3)). The mean decline in forced vital capacity (FVC) was 33 mL/year among inactive participants and 31 mL/year in active participants (difference: −2 mL/year (95% CI: −11 to 7)). The mean decline in FEV1 /FVC ratio was 0.36%/year among inactive participants and 0.22%/year in active participants (difference: −0.14%/year (95% CI: −0.27 to −0.01)). The mean decline in peak expiratory flow (PEF) was 14 mL/year among the inactive participants and 10 mL/year in active participants (difference: −4 mL/year (95% CI: −9 to 1)). Conclusion We observed slightly less decline in lung function in physically active than inactive participants with asthma, particularly for FEV1, FEV1/FVC ratio and PEF.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".