Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: a systematic review and modelling analysis
Bibliographic record
Abstract
Background Chronic obstructive pulmonary disease (COPD) is an increasingly important cause of morbidity, disability, and mortality worldwide. We aimed to estimate global, regional, and national COPD prevalence and risk factors to guide policy and population interventions. Methods For this systematic review and modelling study, we searched MEDLINE, Embase, Global Health, and CINAHL, for population-based studies on COPD prevalence published between Jan 1, 1990, and Dec 31, 2019. We included data reported using the two main case definitions: the Global Initiative for Chronic Obstructive Lung Disease fixed ratio (GOLD; FEV 1 /FVC<0·7) and the lower limit of normal (LLN; FEV 1 /FVC Findings We identified 162 articles reporting population-based studies conducted across 260 sites in 65 countries. In 2019, the global prevalence of COPD among people aged 30–79 years was 10·3% (95% CI 8·2–12·8) using the GOLD case definition, which translates to 391·9 million people (95% CI 312·6–487·9), and 7·6% (5·8–10·1) using the LLN definition, which translates to 292·0 million people (219·8–385·6). Using the GOLD definition, we estimated that 391·9 million (95% CI 312·6–487·9) people aged 30–79 years had COPD worldwide in 2019, with most (315·5 million [246·7–399·6]; 80·5%) living in LMICs. The overall prevalence of GOLD-COPD among people aged 30–79 years was the highest in the Western Pacific region (11·7% [95% CI 9·3–14·6]) and lowest in the region of the Americas (6·8% [95% CI 5·6–8·2]). Globally, male sex (OR 2·1 [95% CI 1·8–2·3]), smoking (current smoker 3·2 [2·5–4·0]; ever smoker 2·3 [2·0–2·5]), body-mass index of less than 18·5 kg/m 2 (2·2 [1·7–2·7]), biomass exposure (1·4 [1·2–1·7]), and occupational exposure to dust or smoke (1·4 [1·3–1·6]) were all substantial risk factors for COPD. Interpretation With more than three-quarters of global COPD cases in LMICs, tackling this chronic condition is a major and increasing challenge for health systems in these settings. In the absence of targeted population-wide efforts and health system reforms in these settings, many of which are under-resourced, achieving a substantial reduction in the burden of COPD globally might remain a difficult task. Funding National Institute for Health Research and Health Data Research UK.
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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 | 0.019 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.034 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".