Prevalence of COPD among population above 30 years in India: A systematic review and meta-analysis
Bibliographic record
Abstract
By 2030, Sustainable Development Goal 3.4 aims to reduce the premature mortality caused by non-communicable diseases through prevention and treatment. Chronic obstructive pulmonary disease is the second leading cause of mortality and disability-adjusted life years in India. This review was conducted to estimate the prevalence of COPD using systematic review and meta-analysis technique.Search was conducted using six databases for studies on COPD among population above 30 years in India between years 2000 to 2020. Cross-sectional and cohort studies reporting prevalence of COPD and associated risk factors were included in the present review. Screening and data extraction was done by two authors independently. Studies were appraised for quality using the modified New Castle Ottawa scale and reporting quality was assessed using STROBE guidelines.Our search returned 8973 records, from which 23 records fulfilled the eligibility criteria. Overall, the prevalence of COPD among population aged 30 years and above in India was 7%. Risk factors like active and passive smoking, biomass fuel exposure, environmental tobacco smoke, occupational exposure to dust, indoor and outdoor pollution, and increasing age were reported to have a significant association with COPD among Indian population.Our findings suggest the need for a multicentric national-level research study to understand COPD burden and its contributing risk factors. The findings also suggest the need for COPD sensitive health literacy program focused on early screening and primary prevention of risk factors for COPD, which may help early initiation of self-management practices, that are crucial for better quality of life.
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 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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".