The relationship between body fat and respiratory function in young adults
Bibliographic record
Abstract
The relationship between adiposity and respiratory function is poorly understood. Most studies investigating this have used indirect measures of body fat and few have assessed how changes in adiposity influence lung function.Body fat measured by bio-electrical impedance analysis, body mass index, waist circumference, spirometry, body plethysmography and transfer factor were measured at ages 32 and 38 years in 361 non-smoking, non-asthmatic participants from a population-based birth cohort.Higher percentage body fat was associated with lower spirometric and plethysmographic lung volumes, but not with airflow obstruction, or transfer factor at 32 years. Changes in adiposity between ages 32 and 38 years were inversely associated with changes in lung volumes. These associations were generally stronger in men than women, but an association between increasing adiposity and lower airway function (forced expiratory volume in 1 s/forced vital capacity) was only found in women. Similar associations were found for body mass index and waist circumference.Higher percentage body fat is associated with lower lung volumes. Direct and indirect measures of adiposity had similar associations with lung function. Adiposity had a greater effect on lung volumes in men than women but was associated with airway function only in women. There was little evidence that adiposity influenced transfer factor.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".