The effect of occupational exposure to organic dust on lung function parameters among African industrial workers: a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Inadequate ventilation and improper use of personal protective equipment are often observed in many occupational settings with a high risk of dust and other fine particle exposure. Workers who are exposed to dust at work may suffer from respiratory difficulties. Previous systematic reviews on organic dust exposure and its association with respiratory health outcomes did not provide a comprehensive assessment. Therefore, the objective of this systematic review and meta-analysis was to summarize the reported effects of organic dust exposure on lung function parameters among African industrial workers. Methods A compressive literature search was conducted in PubMed, MEDLINE, Google Scholar, Embase, the Web of Science, African Journals Online, and ScienceDirect databases to identify relevant studies for the review. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies. The lung function indices including forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), the FEV1/FVC ratio, and peak expiratory flow rate (PEFR) were obtained from primary studies and analyzed using STATA version 17. The I2 test was used to assess the heterogeneity of studies. We used a random-effects model to estimate the pooled standard mean difference in lung function indices between organic dust-exposed and non-exposed industrial workers. To analyze publication bias, funnel plots and Egger’s test were applied. Results In this systematic review and meta-analysis, 32 studies involving 7,085 participants were included from 13,529 identified studies. The estimated mean differences with 95% confidence intervals were as follows: −0.53 [−0.83 to −0.36] L for FVC, −0.60 [−0.77 to −0.43] L for FEV1, −0.43 [−0.57, −0.29] L for FEV1/FVC, and −0.69 [−0.88 to −0.50] L/min for PEFR. Conclusion This systematic review and meta-analysis revealed that the lung function indices, such as FVC, FEV1, FEV1/FVC, and PEFR, were statistically significantly lower among organic dust-exposed industrial workers compared to non-exposed industrial workers. Therefore, effective dust control measures should be implemented to protect workers from exposure to organic dust. Systematic Review Registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024527139 .
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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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.037 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".