A Strong Graded Relationship between Level of Obesity and COPD: Findings from a National Population-Based Study of Lifelong Nonsmokers
Bibliographic record
Abstract
Factors associated with chronic obstructive pulmonary disease (COPD) among never-smokers have received little research attention. One potential risk factor for COPD is obesity, which is of particular importance in light of the global obesity epidemic. The objective of this study was to investigate the association between COPD and levels of obesity in a nationally representative sample of non-Hispanic white never-smokers. Data were drawn from the 2012 Center for Disease Control's Behavioral Risk Factor Surveillance System (BRFSS). Pearson's chi-square tests and logistic regression analyses were conducted in a large nationally representative sample of non-Hispanic white respondents aged 50 and over (76,004 women; 37,618 men) who reported that they had never smoked. A dose-response relationship was observed for both men and women: the prevalence of COPD increased from 2.5% in men and 3.5% in women who were of a healthy weight (BMI < 25) to 7.6% in men and 13.4% in women who had a BMI of 40 or higher. Even after adjusting for 7 potential confounds (e.g., age, education, and income), the odds of COPD were 3.21 higher for men (95% CI = 2.46, 4.20) and 4.00 higher for women with class III obesity (95% CI = 3.52, 4.55) in comparison with those of healthy weight. Regular screening for COPD is warranted in never-smoking obese patients who are aged 50 and over. Future research is needed to investigate plausible mechanisms for this association, including (1) the role of chronic inflammation associated with obesity and (2) the impact of central obesity on respiratory system mechanics.
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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 | 0.001 | 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".