Influence of Body Composition on Lung Function and Respiratory Muscle Strength in Children With Obesity
Bibliographic record
Abstract
BACKGROUND: Obesity affects lung function and respiratory muscle strength. The aim of the present study was to assess lung function and respiratory muscle strength in children with obesity and determine the influence of body composition on these variables. METHODS: A cross-sectional study was conducted involving 75 children (40 with obesity and 35 within the ideal weight range) aged 6 - 10 years. Body mass index, z score, waist circumference, body composition (tetrapolar bioimpedance), respiratory muscle strength and lung function (spirometry) were evaluated. RESULTS: Children with obesity exhibited larger quantities of both lean and fat mass in comparison to those in the ideal weight range. No significant differences were found between groups regarding the respective reference values for respiratory muscle strength. Male children with obesity demonstrated significantly lower lung function values (forced expiratory volume in the first second % (FEV1%) and FEV1/forced vital capacity % (FVC%) : 93.76 ± 9.78 and 92.29 ± 3.8, respectively) in comparison to males in the ideal weight range (99.87 ± 9.72 and 96.31 ± 4.82, respectively). The regression models demonstrated that the spirometric variables were influenced by all body composition variables. CONCLUSION: Children with obesity demonstrated a reduction in lung volume and capacity. Thus, anthropometric and body composition characteristics may be predictive factors for altered lung function.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".