The Impact of Chronic Obstructive Pulmonary Disease on Work Loss in the United States
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD) is a rapidly growing public health problem in the United States and elsewhere. Although direct costs of COPD are well documented, the impact of COPD and its severity on labor force participation is not well known. Using population-based data from the Third National Health and Nutrition Examination Survey (NHANES III), we determined the adjusted relationship between COPD (and its severity) and labor force participation in the U.S. We used data from 12,436 participants involved in NHANES III; 1,073 of these participants (8.6% of the total) reported COPD. These participants were 3.9% (95% confidence interval, 1.3% to 6.4%) less likely to be in the labor force than those without COPD. Increasing severity of COPD was associated with decreased probability of being in the labor force (p for linear trend = 0.001). Mild, moderate, and severe COPD was associated with a 3.4%, 3.9%, and 14.4% reduction in the labor force participation rate relative to those without COPD. These data suggest that COPD has a considerable adverse impact on work force participation. Based on these data, we estimate that, in 1994, COPD was responsible for work loss of approximately $9.9 billion in the U.S.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".