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Record W2171448205 · doi:10.1164/ajrccm.165.5.2104055

The Impact of Chronic Obstructive Pulmonary Disease on Work Loss in the United States

2002· article· en· W2171448205 on OpenAlexaff
Don D. Sin, Tania Stafinski, Ying Chu Ng, Neil R. Bell, Philip Jacobs

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsInstitute of Health EconomicsUniversity of Alberta
Fundersnot available
KeywordsCOPDMedicineNational Health and Nutrition Examination SurveyPulmonary diseaseConfidence intervalPopulationPhysical therapyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.023
GPT teacher head0.337
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations148
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Respiratory and Critical Care MedicineSame topicChronic Obstructive Pulmonary Disease (COPD) ResearchFrench-language works237,207