Association between Coalmine Dust and Mortality Risk of Lung Cancer: A Meta‐Analysis
Bibliographic record
Abstract
Background . Evidence on the carcinogenicity of coalmine dust in occupational settings is still conflicting. Therefore, we conducted this research to evaluate the mortality risk of lung cancer for coalminers exposed to occupational dust when compared to population with no or low dust exposure. Methods . Databases of PubMed and Chinese National Knowledge Infrastructure as well as reference lists were searched updated to September 18, 2020. The enrolled articles should report lung cancer mortality risk for coalminers exposed to occupational dust. Basic information was extracted such as the author and publication year, area and ethnicity, the type and estimates of outcome, duration of follow‐up, and the study design. The checklists from Agency for Healthcare Research and Quality and the Newcastle‐Ottawa Scale were used for the assessment of quality and bias risk for descriptive studies, cohort studies, and case control studies, respectively. The overall relative risks were calculated while Begg’s and Egger’s tests and sensitivity analysis were performed to explore potential heterogeneity sources. Metaregression and subgroup analyses were also conducted to give more detailed information for the correlation between dust exposure and lung cancer mortality. Results . A total of 19 articles with 22 different studies (descriptive study, case control study, and cohort study) including 8909 observed deaths from 1964 to 2017 were enrolled with a significant heterogeneity ( I 2 = 95 % , P < 0.001). The pooled relative risk of mortality from lung cancer was 1.16 (1.03‐1.30) for coalminers. Results of metaregression analysis indicated that the high heterogeneity among these enrolled studies might be caused by the ethnicity differences ( P = 0.011). Subgroup analysis also indicated that the pooled estimate for Asian population in China was 4.94 (3.95‐6.17) with I 2 = 39.3 % and P = 0.192. All these results suggested that exposure to occupational dust would significantly increase the mortality risk of lung cancer, especially for Asian population in China, which should be measured and controlled more strictly. Discussion . This systematic review and meta‐analysis provides high‐quality evidence that exposure to occupational dust might increase the mortality risk of lung cancer, especially for Asian populations in China. The magnitude of this effect is of major public health importance in view of the ubiquitous existence of coalmining industry in China and even in the world. However, these pooled estimates should be interpreted cautiously because of the high heterogeneity among these publications. Other . This study was supported by the National Key Research and Development Program of China (Grant No. 2016YFC1302501).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".