Associations between airway hyperresponsiveness, obesity and lipoproteins in a longitudinal cohort
Bibliographic record
Abstract
BACKGROUND: Epidemiological data have linked obesity with an increased risk of asthma, but the mechanisms responsible for this relationship remain unknown. One possible mechanism, which has received little attention, could be the effect of cholesterol metabolism on airway smooth muscle function. The present study investigated the association between airway hyperresponsiveness (AHR) to methacholine and body mass index (BMI) and plasma lipoproteins [low-density lipoprotein (LDL), high-density lipoprotein (HDL) and total cholesterol]. METHODS: Associations between AHR, BMI and plasma lipoproteins were assessed in a population-based cohort at ages 14 and 20 years. RESULTS: In unadjusted analyses, higher LDL cholesterol levels at age 14 were associated with AHR at age 20 in both sexes (P < 0.05). HDL, LDL/HDL ratio and total cholesterol were not associated with AHR. In multiple regression analyses adjusted for sex, lung function, smoking and asthma, only higher levels of BMI at age 14 or 20 years were significantly associated with increased AHR at age 20 years, while neither LDL, HDL and LDL/HDL ratio nor total cholesterol were significantly associated with AHR. CONCLUSION: We confirmed that in teenagers there is a strong association between BMI and AHR to methacholine. This association seems to be independent of the plasma lipoprotein levels at that age.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".